GeoT Standard (2.1): Up to 50 waters can be processed at the same time. Multicomponent aqueous geochemical speciation and solute geothermometry with deep fluid reconstruction. As an option, GeoT allows for the re-equilibration of certain minerals while making reservoir temperature estimations.
\r\n\r\nGeoT improves the prediction of geothermal reservoir temperatures using full and integrated chemical analyses of geothermal fluids by implementing Berkeley Lab’s multicomponent geothermometry method. This approach represents an improvement over classic geothermometers for fluids that have not fully equilibrated with reservoir minerals and/or that have been subject to processes such as dilution and gas loss.
\r\n\r\nCurrent software versions allow for the reaction of selected minerals while making temperature estimations, for cases when some minerals (such as carbonates) are suspected to have re-equilibrated with thermal fluids ascending to the surface. Another option is the iterative estimation of steam fraction (and correction for lost steam when making temperature estimations) by assuming iso-enthalpic boiling starting at the estimated reservoir temperature.
\r\n\r\nFor the full text of each license type go here.
\r\n","short":"Prediction of geothermal reservoir temperatures (50 waters)"},"id":4719792,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/2_GeoT_Master.png","isFeatured":false,"isHero":false,"name":"GeoT Standard (2.1)","path":"geoenvironment/water-and-the-environment","pcode":"geot_standard_2-1","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/GeoT_Master.png"},"-L3dFjhrDgwLTPA9qtGa":{"description":{"long":"
TOUGH+: solves mass and energy balance equations that describe fluid and heat flow in general multiphase, multicomponent, porous-media systems
\r\n\r\nTOUGH+, a re-engineered, modular design of TOUGH2, offers new capabilities including an extended range for the thermodynamic properties of water to include ice. This enables modeling of freezing and thawing in permafrost regions and the simulation of processes in hydrate-bearing sediments.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"TOUGH+ extended range for the thermodynamic properties of water"},"id":4723397,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/Toughplus.png","isFeatured":false,"isHero":false,"name":"TOUGH+ Hydrate 1.5 (Executable)","path":"tough/tough+","pcode":"toughplus_hydrate_executable","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Toughplus.png"},"-L3dGRw5bZjTwazi6ylL":{"description":{"long":"
TOUGH+: solves mass and energy balance equations that describe fluid and heat flow in general multiphase, multicomponent, porous-media systems
\r\n\r\nTOUGH+, a re-engineered, modular design of TOUGH2, offers new capabilities including an extended range for the thermodynamic properties of water to include ice. This enables modeling of freezing and thawing in permafrost regions and the simulation of processes in hydrate-bearing sediments.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"TOUGH+ extended range for the thermodynamic properties of water"},"id":4723398,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/3_Tough%2B.png","isFeatured":false,"isHero":false,"name":"TOUGH+ Hydrate 1.5 (Source)","path":"tough/tough+","pcode":"toughplus_hydrate_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Toughplus.png"},"-L3dHuTKzOFbYQlPoGNq":{"description":{"long":"
TOUGH+: solves mass and energy balance equations that describe fluid and heat flow in general multiphase, multicomponent, porous-media systems
\r\n\r\nTOUGH+, a re-engineered, modular design of TOUGH2, offers new capabilities including an extended range for the thermodynamic properties of water to include ice. This enables modeling of freezing and thawing in permafrost regions and the simulation of processes in hydrate-bearing sediments.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"TOUGH+ extended capabilities for gas-bearing formations"},"id":4719796,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/Tough%2B.png","isFeatured":false,"isHero":false,"name":"TOUGH+ RealGasBrine 1.0 (Executable)","path":"tough/tough+","pcode":"toughplus_realgasbrine_executable","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Toughplus.png"},"-L5IE7pq2Iw-9vkWHqkq":{"description":{"long":"
TOUGH3 V 1.12 enables simulations for predictive modeling nonisothermal multiphase flow in fractured porous media on desktop computers using a single code. With its improved capabilities, usability and output options, TOUGH3 is a more robust and efficient tool for solving difficult and computationally demanding problems in diverse scientific and practical applications related to subsurface flow modeling.
\r\n
\r\nNote:Binary (executable) files are available for PC. For binaries for Mac or Linux, purchase the source code and compile the code.
\r\n
\r\nTOUGH3 equation-of-state modules:
\r\nTOUGH3 EOS1 - Water, water with tracer, heat
\r\nTOUGH3 EOS2 - Water, CO2, heat
\r\nTOUGH3 EOS3 - Water, air, heat
\r\nTOUGH3 EOS4 - Water, air, heat, with vapor pressure lowering
\r\nTOUGH3 EOS5 - Water, hydrogen, heat
\r\nTOUGH3 EOS7 - Water, brine, air, heat
\r\nTOUGH3 EOS7r - Water, brine, air, radionuclide1, radionuclide2, heat
\r\nTOUGH3 EOS7C - Water, brine, CO2 or N2, tracer, CH4, and heat
\r\nTOUGH3 EOS7CA - Water, brine, NCG (CO2, N2, or CH4), gas tracer, air, heat (see flyer)
\r\nTOUGH3 EOS8 - Water, air, oil
\r\nTOUGH3 EOS9 - Water (Richards equation)
\r\nTOUGH3 EWASG - Water, NaCl, NCG, heat
\r\nTOUGH3 ECO2N - Water, brine, CO2
\r\nTOUGH3 ECO2M - Water, brine, CO2 (multiphase)
\r\nTOUGH3 TMVOC - Water, VOCs, NCGs
\r\nTOUGH3 EOS7MG - Water, brine, gas
For the full text of each license type go here.
\r\n\r\n","short":"Latest basic simulator for nonisothermal multiphase flow in fractured porous media"},"id":4723394,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/1_Tough3.png","isFeatured":true,"isHero":false,"name":"TOUGH3 1.12 (Source)","path":"tough/tough-3","pcode":"TOUGH3_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Tough3.png"},"-L5IEDbaoxqv6T6Los_O":{"description":{"long":"
TOUGH3 V 1.12 enables simulations for predictive modeling nonisothermal multiphase flow in fractured porous media on desktop computers using a single code. With its improved capabilities, usability and output options, TOUGH3 is a more robust and efficient tool for solving difficult and computationally demanding problems in diverse scientific and practical applications related to subsurface flow modeling.
\r\n
\r\nNote:Binary (executable) files are available for PC. For binaries for Mac or Linux, purchase the source code and compile the code.
\r\n
\r\nTOUGH3 equation-of-state modules:
\r\nTOUGH3 EOS1 - Water, water with tracer, heat
\r\nTOUGH3 EOS2 - Water, CO2, heat
\r\nTOUGH3 EOS3 - Water, air, heat
\r\nTOUGH3 EOS4 - Water, air, heat, with vapor pressure lowering
\r\nTOUGH3 EOS5 - Water, hydrogen, heat
\r\nTOUGH3 EOS7 - Water, brine, air, heat
\r\nTOUGH3 EOS7r - Water, brine, air, radionuclide1, radionuclide2, heat
\r\nTOUGH3 EOS7C - Water, brine, CO2 or N2, tracer, CH4, and heat
\r\nTOUGH3 EOS7CA - Water, brine, NCG (CO2, N2, or CH4), gas tracer, air, heat (see flyer)
\r\nTOUGH3 EOS8 - Water, air, oil
\r\nTOUGH3 EOS9 - Water (Richards equation)
\r\nTOUGH3 EWASG - Water, NaCl, NCG, heat
\r\nTOUGH3 ECO2N - Water, brine, CO2
\r\nTOUGH3 ECO2M - Water, brine, CO2 (multiphase)
\r\nTOUGH3 TMVOC - Water, VOCs, NCGs
\r\nTOUGH3 EOS7MG - Water, brine, gas
For the full text of each license type go here.
\r\n\r\n","short":"Latest basic simulator for nonisothermal multiphase flow in fractured porous media"},"id":4723393,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/Tough3.png","isFeatured":true,"isHero":false,"name":"TOUGH3 1.12 (Executable)","path":"tough/tough-3","pcode":"TOUGH3_executable","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Tough3.png"},"-L5IbjSbfqcIz4W7ob3j":{"description":{"long":"
TOUGH+: solves mass and energy balance equations that describe fluid and heat flow in general multiphase, multicomponent, porous-media systems
\r\n\r\nTOUGH+, a re-engineered, modular design of TOUGH2, offers new capabilities including an extended range for the thermodynamic properties of water to include ice. This enables modeling of freezing and thawing in permafrost regions and the simulation of processes in hydrate-bearing sediments.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"TOUGH+ extended capabilities for gas-bearing formations"},"id":4723399,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/7_Tough%2B.png","isFeatured":false,"isHero":false,"name":"TOUGH+ RealGasBrine 1.0 (Source)","path":"tough/tough+","pcode":"toughplus_RealGasBrine_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Toughplus.png"},"-L5IbtHv3h5qSeJiwX4C":{"description":{"long":"\r\n\r\n
Parallel version of TOUGH+Hydrate. Includes parallel version of TOUGH+Core.
\r\n\r\nTOUGH+: solves mass and energy balance equations that describe fluid and heat flow in general multiphase, multicomponent, porous-media systems
\r\n\r\nTOUGH+, a re-engineered, modular design of TOUGH2, offers new capabilities including an extended range for the thermodynamic properties of water to include ice. This enables modeling of freezing and thawing in permafrost regions and the simulation of processes in hydrate-bearing sediments.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"Parallel version of TOUGH+Hydrate"},"id":4721243,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/5_Tough%2B.png","isFeatured":false,"isHero":false,"name":"pT+H - TOUGH+Hydrate Parallel Version","path":"tough/tough+","pcode":"pT_H_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Toughplus.png"},"-L5IcXFDHhkfmVhvwzwq":{"description":{"long":"
iTOUGH2 (inverse TOUGH2): inverse modeling capabilities for TOUGH codes for predictive modeling, inverse modelity, sensitivity analysis, data-worth analysis, and uncertainty propagation analysis
\r\n\r\niTOUGH2 automatically calibrates a TOUGH2 (or other) model against observed data to measure the difference between calculation and observation while a minimization algorithm proposes new parameter sets that iteratively improve the match.
\r\n\r\n\r\n
For the full text of each license type go here.
\r\nIf you have any technical software questions, please email the TOUGH developers here.
\r\n","short":"Inverse modeling capabilities for TOUGH codes"},"id":4723396,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/1_iTough2.png","isFeatured":false,"isHero":false,"name":"iTOUGH2 v7.1 Executable","path":"tough/itough2","pcode":"itough2_executable","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/iTough2.png"},"-L5IcdlmvbU9fz7nhd-W":{"description":{"long":"iTOUGH2 (inverse TOUGH2): inverse modeling capabilities for TOUGH codes for predictive modeling, inverse modelity, sensitivity analysis, data-worth analysis, and uncertainty propagation analysis.
\r\n\r\niTOUGH2 automatically calibrates a TOUGH2 (or other) model against observed data to measure the difference between calculation and observation while a minimization algorithm proposes new parameter sets that iteratively improve the match.
\r\n\r\n\r\n
For the full text of each license type go here.
\r\n\r\n","short":"Inverse modeling capabilities for TOUGH codes"},"id":4719795,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/iTough2.png","isFeatured":false,"isHero":false,"name":"iTOUGH2 v7.1 Source","path":"tough/itough2","pcode":"itough2_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/iTough2.png"},"-L5IcyzRM9ffu-X0f3tQ":{"description":{"long":"
WinGridder V3.0 is a Windows-based graphical mesh generator for TOUGH. It allows the generation and visualization of complex, unstructured finite volume meshes, which may internal boundaries, include fault offsets, boreholes, etc.
\r\n\r\nGraphical mesh generator.
\r\n\r\nExecutable only.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"WinGridder, Graphical mesh generator"},"id":4719804,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/ToughAC.png","isFeatured":false,"isHero":false,"name":"WinGridder 3.0 (Executable)","path":"tough/tough-ancillary-codes","pcode":"wingridder_executable","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/ToughAC.png"},"-L5IdC6mvvUZ3iR4hYRp":{"description":{"long":"
Computes real gas properties.
\r\n\r\nMore information can be found on the WebGasEOS site.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n\r\n","short":"Computes real gas properties"},"id":4723400,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/9_ToughAC.png","isFeatured":false,"isHero":false,"name":"GasEOS - Ancillary code: GasEOS 2.0 (Source)","path":"tough/tough-ancillary-codes","pcode":"gaseos_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/ToughAC.png"},"-L5IdVz7nmHzIHPYJm8I":{"description":{"long":"
An equation-of-state module for CO2 or N2 in Methane (CH4), enhanced to include Enhanced Coal Bed Methane (ECBM) modifications, in which CO2 is pumped into methane-rich coal beds.
\r\n\r\nWater, brine, CO2 or N2, tracer, CH4, and heat, with ECBM isotherm and Dusty Gas Model
\r\n\r\nIf you purchased a Academic/Government/Collaboration license, the executable TOUGH ancillary codes are already included. Purchase TOUGH ancillary codes here if you purchased a TOUGH2 Commercial license.
\r\n\r\nFor the full text of each license type go here.
\r\nAn equation-of-state module for CO2 or N2 in Methane (CH4), enhanced to include Enhanced Coal Bed Methane (ECBM) modifications, in which CO2 is pumped into methane-rich coal beds.
\r\n\r\nWater, brine, CO2 or N2, tracer, CH4, and heat, with ECBM isotherm and Dusty Gas Model
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n\r\n","short":"Equation-of-state module for CO2 or N2 in methane, enhanced to include Enhanced Coal Bed Methane (ECBM) modifications"},"id":4723401,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/6_ToughAC.png","isFeatured":false,"isHero":false,"name":"EOS7C-ECBM - Ancillary code: EOS7C-ECBM 1.0 (Source)","path":"tough/tough-ancillary-codes","pcode":"eoc7c_ecbm_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/ToughAC.png"},"-L5IdghvPJV1eIrswlQK":{"description":{"long":"
A coupled wellbore and reservoir model for simulating the dynamics of CO2 injection through wellbores.
\r\n\r\nTOUGH2-ECO2N with multiphase wellbore simulator.
\r\n\r\nIf you purchased a Academic/Goverment/Collaboration license, the T2Well-ECO2N executable is already included. If you purchased a Commercial license for the source code only and want executable code, purchase the T2Well-ECO2N executable here.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"A coupled wellbore and reservoir model for simulating the dynamics of CO2 injection through wellbores"},"id":4719803,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/1_ToughAC.png","isFeatured":false,"isHero":false,"name":"T2Well - Ancillary code: T2Well-ECO2N 1.02 (Executable) ","path":"tough/tough-ancillary-codes","pcode":"t2_eco2n_executable","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/ToughAC.png"},"-L5Idlpw3DTs2LXhTrHR":{"description":{"long":"
A coupled wellbore and reservoir model for simulating the dynamics of CO2 injection through wellbores.
\r\n\r\nTOUGH2-ECO2N with multiphase wellbore simulator
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"A coupled wellbore and reservoir model for simulating the dynamics of CO2 injection through wellbores"},"id":4723899,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/2_ToughAC.png","isFeatured":false,"isHero":false,"name":"T2Well - Ancillary code: T2Well-ECO2N 1.02 (Source) ","path":"tough/tough-ancillary-codes","pcode":"t2_eco2n_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/ToughAC.png"},"-L5K7ogpC92fpGMgBG_r":{"description":{"long":"
Simulates flow and transport of an arbitrary number of non-volatile tracers (solutes and/or colloids) in the subsurface. The module first solves the Richards equation and obtains the flow regime; then transport equations corresponding to the tracers/colloids are then solved sequentially.
\r\n\r\nWater, tracers, colloids.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"Simulates flow and transport of water, tracers, colloids"},"id":4719802,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/7_ToughAC.png","isFeatured":false,"isHero":false,"name":"EOS9nT - Ancillary code: EOS9nT 2.11 (Source) ","path":"tough/tough-ancillary-codes","pcode":"eos9nt_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/ToughAC.png"},"-L5K9W9rABjP9KKmtjfW":{"description":{"long":"
GeoT Limited (2.1): Only two (2) waters can be processed at the same time. Same functionality as GeoT Standard (2.1): Multicomponent aqueous geochemical speciation and solute geothermometry with deep fluid reconstruction. As an option, GeoT allows for the re-equilibration of certain minerals while making reservoir temperature estimations.
\r\n\r\nGeoT improves the prediction of geothermal reservoir temperatures using full and integrated chemical analyses of geothermal fluids by implementing Berkeley Lab’s multicomponent geothermometry method. This approach represents an improvement over classic geothermometers for fluids that have not fully equilibrated with reservoir minerals and/or that have been subject to processes such as dilution and gas loss.
\r\n\r\nCurrent software versions allow for the reaction of selected minerals while making temperature estimations, for cases when some minerals (such as carbonates) are suspected to have re-equilibrated with thermal fluids ascending to the surface. Another option is the iterative estimation of steam fraction (and correction for lost steam when making temperature estimations) by assuming iso-enthalpic boiling starting at the estimated reservoir temperature.
\r\n\r\nFor the full text of each license type go here.
\r\n","short":"Prediction of geothermal reservoir temperatures (2 waters)"},"id":4719793,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/1_GeoT_Master.png","isFeatured":false,"isHero":false,"name":"GeoT Limited (2.1)","path":"geoenvironment/water-and-the-environment","pcode":"geot_limited_2-1","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/GeoT_Master.png"},"-L5K9_QSWDtsdp1mw8it":{"description":{"long":"
iGeoT (v1.0): Same functionality as GeoT Standard (2.1): Multicomponent aqueous geochemical speciation and solute geothermometry with deep fluid reconstruction. As an option, GeoT allows for the re-equilibration of certain minerals while making reservoir temperature estimations.
\r\n\r\niGeoT also
\r\n\r\nGeoT improves the prediction of geothermal reservoir temperatures using full and integrated chemical analyses of geothermal fluids by implementing Berkeley Lab’s multicomponent geothermometry method. This approach represents an improvement over classic geothermometers for fluids that have not fully equilibrated with reservoir minerals and/or that have been subject to processes such as dilution and gas loss.
\r\n\r\nCurrent software versions allow for the reaction of selected minerals while making temperature estimations, for cases when some minerals (such as carbonates) are suspected to have re-equilibrated with thermal fluids ascending to the surface. Another option is the iterative estimation of steam fraction (and correction for lost steam when making temperature estimations) by assuming iso-enthalpic boiling starting at the estimated reservoir temperature.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n\r\n
","short":"GeoT Standard with additional functionality"},"id":4719794,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/GeoT_Master.png","isFeatured":false,"isHero":false,"name":"iGeoT (v1.0)","path":"geoenvironment/water-and-the-environment","pcode":"igeot_1-0","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/GeoT_Master.png"},"-LD8T0B44Mli2NCupQbI":{"description":{"long":"
TOUGH+: solves mass and energy balance equations that describe fluid and heat flow in general multiphase, multicomponent, porous-media systems
\r\n\r\nTOUGH+, a re-engineered, modular design of TOUGH2, offers new capabilities including an extended range for the thermodynamic properties of water to include ice. This enables modeling of freezing and thawing in permafrost regions and the simulation of processes in hydrate-bearing sediments.
\r\n\r\nTOUGH+ Core is offered with Hydrate V 1.5 and RealGasBrine V 1.0.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"TOUGH+ for hydrate-and gas-bearing formations"},"id":4735422,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/4_Tough%2B.png","isFeatured":false,"isHero":false,"name":"TOUGH+ Hydrate 1.5 & RealGasBrine 1.0 (Source)","path":"tough/tough+","pcode":"toughplus_bundled_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Toughplus.png"},"-LD8THs1Cg895YlPzgmm":{"description":{"long":"
TOUGH+: solves mass and energy balance equations that describe fluid and heat flow in general multiphase, multicomponent, porous-media systems
\r\n\r\nTOUGH+, a re-engineered, modular design of TOUGH2, offers new capabilities including an extended range for the thermodynamic properties of water to include ice. This enables modeling of freezing and thawing in permafrost regions and the simulation of processes in hydrate-bearing sediments.
\r\n\r\nTOUGH+ Core is offered with Hydrate V 1.5 and RealGasBrine V 1.0.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"TOUGH+ for hydrate-and gas-bearing formations"},"id":4735428,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/6_Tough%2B.png","isFeatured":false,"isHero":false,"name":"TOUGH+ Hydrate 1.5 & RealGasBrine 1.0 (Executable)","path":"tough/tough+","pcode":"toughplus_bundled_executable","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Toughplus.png"},"-M7O9fGtSFxCtYCaQgAP":{"description":{"long":"
TOGA V 1.0 (TOUGH Oil, Gas, Aqueous) is a numerical reservoir simulator for modeling non-isothermal flow and transport of water, CO2, multicomponent oil, and related gas components for applications including CO2-enhanced oil recovery (CO2-EOR) and geologic carbon sequestration in depleted oil and gas reservoirs.
\r\n\r\nAll components (e.g., CO2, H2O, and n hydrocarbon components) are allowed to be present in all phases (aqueous, gaseous, and oil) in simulations. TOGA uses a multiphase version of Darcy’s law to model the flow and transport of multicomponent mixtures with up to three phases over a range of pressures and temperatures appropriate to hydrocarbon recovery and geologic carbon sequestration systems in porous media. Transport of the gaseous and dissolved components is by advection and Fickian molecular diffusion.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"TOUGH for Oil, Gas, Aqueous applications"},"id":29465387,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/toga_4%20Copy1.png","isFeatured":true,"isHero":false,"name":"TOGA Executable 1.0","path":"tough/toga","pcode":"toga_executable","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/toga_4_342.png"},"-M7O9nxDzu1kZYo5uPi3":{"description":{"long":"
TOGA V1.0 (TOUGH Oil, Gas, Aqueous) is a numerical reservoir simulator for modeling non-isothermal flow and transport of water, CO2, multicomponent oil, and related gas components for applications including CO2-enhanced oil recovery (CO2-EOR) and geologic carbon sequestration in depleted oil and gas reservoirs.
\r\n\r\nAll components (e.g., CO2, H2O, and n hydrocarbon components) are allowed to be present in all phases (aqueous, gaseous, and oil) in simulations. TOGA uses a multiphase version of Darcy’s law to model the flow and transport of multicomponent mixtures with up to three phases over a range of pressures and temperatures appropriate to hydrocarbon recovery and geologic carbon sequestration systems in porous media. Transport of the gaseous and dissolved components is by advection and Fickian molecular diffusion.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"TOUGH for Oil, Gas, Aqueous applications"},"id":29807204,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/toga_4.png","isFeatured":true,"isHero":false,"name":"TOGA Source 1.0","path":"tough/toga","pcode":"toga_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/toga_4.png"},"-MBolJfMuLr0shzhes38":{"description":{"long":"
basecRAWller implements the first base caller for nanopore data that calls bases directly from raw data. The basecRAWller algorithm has two major advantages over current nanopore base calling software: (1) streaming base calling and (2) base calling from information rich raw signal. The ability to perform truly streaming base calling as signal is received from the sequencer can be very powerful as this is one of the major advantages of this technology as compared to other sequencing technologies.
\r\n\r\nFor the full text of the license type and definitions go here.
\r\n\r\n\r\n
TOUGHREACT V4.13-OMP: A 3-D Multiphase Reactive-Transport Simulator for Porous and Fractured Media
\r\n\r\nTOUGHREACT V4.13-OMP is a major new release of TOUGHREACT that includes many new features and parallelization of the most CPU-intensive calculations in reactive-transport simulations. It adds the following capabilities and improvements to V3.32-OMP:
\r\nUpgrade of ECO2N to V2, covering a temperature range up to 300°C\r\n\r\n
For the full product description of TOUGHREACT V4.13-OMP go here.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"Latest release of TOUGHREACT with new features"},"id":37032145,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/1_Toughreact.png","isFeatured":true,"isHero":false,"name":"TOUGHREACT 4.13-OMP (Executable)","path":"tough/toughreact","pcode":"toughreact4_exec","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Toughreact.png"},"-Mv_u3UdFRUTFiJrJHYr":{"description":{"long":"
TOUGHREACT V4.13-OMP: A 3-D Multiphase Reactive-Transport Simulator for Porous and Fractured Media
\r\n\r\nTOUGHREACT V4.13-OMP is a major new release of TOUGHREACT that includes many new features and parallelization of the most CPU-intensive calculations in reactive-transport simulations. It adds the following capabilities and improvements to V3.32-OMP:
\r\nUpgrade of ECO2N to V2, covering a temperature range up to 300°C\r\n\r\n
For the full product description of TOUGHREACT V4.13-OMP go here.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n","short":"Latest release of TOUGHREACT with new features"},"id":37032241,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/2_Toughreact.png","isFeatured":true,"isHero":false,"name":"TOUGHREACT 4.13-OMP (Source)","path":"tough/toughreact","pcode":"toughreact4_source","thumbnail":"https://secure.avangate.com/images/merchant/cb1d78edc3b427d8f919a169d6931636/Toughreact.png"},"-Ni0G9VfGQ1BrJXBP2S4":{"description":{"long":"
Increased sequencing of microbial genomes has revealed that prevailing prokaryotic species assignments can be inconsistent with whole genome information for a significant number of species. The long-standing need for a systematic and scalable species assignment technique can be met by the genome-wide Average Nucleotide Identity (gANI) metric, which is widely acknowledged as a robust measure of genomic relatedness.
\r\n\r\nBerkeley Lab researchers have demonstrated that the combination of gANI and the alignment fraction (AF) between two genomes accurately reflects their genomic relatedness. Berkeley Lab has introduced an efficient implementation of AF,gANI and discuss its successful application to 86.5M genome pairs between 13,151 prokaryotic genomes assigned to 3032 species. Subsequently, by comparing the genome clusters obtained from complete linkage clustering of these pairs to existing taxonomy, Berkeley Lab researchers observed that nearly 18% of all prokaryotic species suffer from anomalies in species definition. The results can be used to explore central questions such as whether microorganisms form a continuum of genetic diversity or distinct species represented by distinct genetic signatures. This precise and objective AF,gANI-based species definition — the MiSI (Microbial Species Identifier) method — can be used to address previous inconsistencies in species classification and as the primary guide for new taxonomic species assignment, supplemented by the traditional polyphasic approach as required.
\r\n\r\np>For more information: https://ipo.lbl.gov/lbnl2014-127/
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Average Nucleotide Identity Calculator for genome sequencing"},"id":42465430,"isFeatured":false,"isHero":false,"name":"ANIcalculator","path":"biosciences/computational-biology","pcode":"ANIcalculator"},"-Ni0GJUU-qRlHGLfZ0Rb":{"description":{"long":"The AR1K project has acquired a variety of datasets in collaboration with Glennoe Farm, including:
\r\n\r\nThe datasets were acquired at the three soybean fields in Glennoe Farm located in Stuttgart, Arkansas. These datasets capture the field-scale spatiotemporal variability of soil and plants as well as their interactions.
\r\n\r\nVariable cost depending on company size.
\r\nContact ipo@lbl.gov to purchase.
For the full text of each license type and definitions go here.
\r\n\r\n\r\n","short":"Data from AR1K (engineering ag through machine learning)"},"id":42465395,"isFeatured":false,"isHero":false,"name":"AR1K (data)","path":"biosciences/biological-sciences-research-tools-and-methods","pcode":"AR1K"},"-Ni0GSFKXDyML6qTvdhE":{"description":{"long":"
A tool that uses machine learning to make further advancements in the field of synthetic biology. The patent-pending Automated Recommendation Tool (ART) uses probabilistic modeling techniques to guide metabolic engineering systematically without requiring a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. ART is built around a unique uncertainty quantification approach and has been demonstrated to have high predictive accuracy. Using ART improved tryptophan titer and productivity by up to 74% and 43%, respectively, compared to the best designs used for algorithm training.
\r\n\r\nLarge Business = Companies with over 50 full-time or part-time employees.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"A machine learning automatied recommendation tool for guiding synthetic biology"},"id":42465400,"isFeatured":false,"isHero":false,"name":"ART (Large Business)","path":"biosciences/synthetic-biology","pcode":"ART"},"-Ni0GewlwuGqBvu48RQJ":{"description":{"long":"Berkeley Analysis and Storage Toolkit (BASTet)
\r\n\r\nAn advanced software library known as that serves as the analysis and storage library for the OpenMSI project. Written in Python, BASTet is an integrated framework for:
\r\n\r\nOpenMSI Arrayed Analysis Tool (OMAAT)
\r\n\r\nTo broaden the use of mass spectrometry imaging, this novel computational software method addresses the challenges of analyzing spatially defined samples in large MSI datasets, by providing support for automatic sample position optimization and ion selection. OMAAT’s algorithm automatically finds outlier data. It is written in Python with an accompanying Jupyter (formerly iPython) notebook and is fully integrated with OpenMSI.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Analysis and storage library for the OpenMSI project"},"id":42465405,"isFeatured":false,"isHero":false,"name":"BASTet - Berkeley Analysis and Storage Toolkit (BASTet) and OpenMSI Arrayed Analysis Tools (OMAAT)","path":"biosciences/biological-sciences-research-tools-and-methods","pcode":"BASTet_OMAAT"},"-Ni0GibHvbp-kO-WnyDA":{"description":{"long":"The Berkeley Anomaly Detection framework is a python module for detecting and identifying anomalies within gamma-ray spectra. The modular design enables quick implementation, testing, comparison, and deployment of different anomaly and identification algorithms. The module is built around a template design pattern that encapsulates common attributes and methods for spectroscopic analysis algorithms. The module currently contains implementations of four algorithms, two of which are common place within the field, and two that novel research products from this effort. One of the novel algorithms is currently state-of-the-art in the field and is the primary novelty of this code base. This algorithm, here referred to as NMF-ID (Non-negative Matrix Factorization for Identification and Detection) uses Poisson NMF for construction of low-rank background models, and also for testing for the presence of anomalous radiological sources with additional bases/templates. This code was used to win the 2018 DOE-NA22 Urban Radiological Search Competition, establishing the NMF-ID algorithm as a promising tool for this type of analysis. Furthermore, the mathematical design of the NMF-ID algorithm was built to produce intuitive and physical background models. As a result, the output from this algorithm is amenable to multi-sensor data fusion, creating opportunities for continued research and development into how this fusion may be achieved and what improvements in sensitivity or applicability result from these developments.
\r\n\r\nFor more information: https://www.osti.gov/biblio/1492928
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Python module for detecting and identifying anomalies within gamma-ray spectra"},"id":42465510,"isFeatured":false,"isHero":false,"name":"BAD - Berkeley Anomaly Detection","path":"imaging/sensors-and-detectors","pcode":"BAD"},"-Ni0Gy70bnmI_Me8lRIz":{"description":{"long":"A suite of build-optimization software tools (BOOST) to streamline the design-build transition in synthetic biology engineering workflows. The BOOST library offers a wide range of capabilities, including:
\r\n\r\nIn addition, by optimizing the design of DNA sequences, the BOOST library can significantly reduce the cost and turnaround time of DNA synthesis, compared to commercial DNA design software tools.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Build optimization software tools for DNA sequence design"},"id":42465390,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/DOE-JGI_BOOSTlogo-800x547px-300x205.jpg","isFeatured":false,"isHero":false,"name":"BOOST","path":"biosciences/computational-biology","pcode":"BOOST"},"-Ni0HGm_EeJ9_lqCyQxD":{"description":{"long":"City Buildings, Energy, and Sustainability (CityBES) is a web-based data and computing platform, focusing on energy modeling and analysis of a city's building stock to support district or city-scale building energy efficiency programs. CityBES uses an international open data standard, CityGML, to represent and exchange 3D city models. CityBES employs EnergyPlus to simulate building energy use and savings from energy efficient retrofits. Other CityBES features include energy benchmarking, district heating and cooling system modeling, rooftop PV analysis, building performance visualization, heat resilience modeling, as well as urban scale mapping of microclimate and heat vulnerability at census tract level. Different from other tools, CityBES uses integrated open and standard 3D city building data and models each individual building using EnergyPlus. CityBES can be used by urban planners, city energy managers, building owners, utilities, energy consultants and researchers.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Energy modeling and analysis of a city's building stock"},"id":42465480,"isFeatured":false,"isHero":false,"name":"CityBES","path":"energy-efficiency/energy","pcode":"CityBES"},"-Ni0HMoI9uSAjpAQUTRw":{"description":{"long":"API for Commercial Building Energy Saver (CBES), for use by businesses, commercial, and residential building owners, operators, and consultants to perform energy benchmarking and retrofit analysis. The software allows them to identify recommendations for additional energy savings and achieving zero-net energy or carbon neutrality goals.
\r\n\r\nIn addition to offering 100+ built-in energy conservation measures with customizable performance and cost data, the latest version, CBES API version 2.0, has new capabilities including renewable technologies (PV, storage), advanced HVAC systems, demand response measures, TDV (Time Dependent Valuation) energy metrics, as well as shading from adjacent buildings and trees or roof obstructions. The API can be used by third party developers and vendors.
\r\n\r\nCBES includes benchmarking capabilities as well as three levels of retrofit analysis (versions available for California and for all U.S. states):
\r\n\r\nBenchmarking: provides an ENERGY STAR score for the building and compares its electric load to peer buildings’ clustered load shapes.
\r\n\r\nLoad Shape Analysis level: identifies potential no- or low-cost building operation improvements based on smart meter data analytics.
\r\n\r\nPreliminary Retrofit Analysis level: uses a custom developed pre-simulated database to assess energy and cost benefits of energy conservation measures.
\r\n\r\nDetailed Retrofit Analysis level: performs detailed building energy modeling (including whole-building and end-use electricity and natural gas use, energy use and cost savings, and payback of each energy conservation measure), estimates onsite PV production, and evaluates onsite battery storage costs/benefits.
\r\n\r\nFor more information please visit https://cbes.lbl.gov/buildings (for the California version) or https://cbespro.lbl.gov (for the U.S. national version)
\r\n\r\nFree for web based system; API available at a cost TBD.
\r\nContact ipo@lbl.gov for API
For the full text of each license type and definitions go here.
\r\n","short":"A web-based toolkit to perform energy benchmarking and retrofit analysis for buildings"},"id":42465470,"isFeatured":false,"isHero":false,"name":"CBES - Commercial Building Energy Saver API 2.0","path":"energy-efficiency/energy","pcode":"CBES_API_2-0"},"-Ni0HS44ieWwS2oADB4M":{"description":{"long":"The CBES App is a web-based toolkit for use by small businesses and building owners and operators of small and medium size commercial buildings to perform energy benchmarking and retrofit analysis for buildings. The CBES App analyzes the energy performance of user's building for pre- and post-retrofit, in conjunction with user's input data, to identify recommended retrofit measures, energy savings and economic analysis for the selected measures. For more information: https://www.osti.gov/doecode/biblio/22453
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"A web-based toolkit to perform energy benchmarking and retrofit analysis for buildings"},"id":42465475,"isFeatured":false,"isHero":false,"name":"CBES - Commercial Building Energy Saver web based system","path":"energy-efficiency/energy","pcode":"CBES_web"},"-Ni0H_ERhalXD5PfcTAo":{"description":{"long":"A database of energy efficiency performance (DEEP) is a presimulated database to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 10 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER [sic] prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air conditioning, plug loads, and domestic hot war. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center (NERSC) of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of the CEC PIER project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users' decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"A presimulated database for quick and accurate assessment of energy retrofit of commercial buildings"},"id":42465495,"isFeatured":false,"isHero":false,"name":"DEEP - Database of Energy Efficiency Performance","path":"energy-efficiency/energy","pcode":"DEEP"},"-Ni0HsyNbqS_bIYCZHPu":{"description":{"long":"The Decision-support and Emissions Prediction Interactive Cities Tool (DEPICT) aims at predicting the cross-sectoral (building construction, operation and vehicles) energy consumption and greenhouse gases emissions at campus and urban scale. It leverages capabilities of multiple modeling tools: EnergyPlus for building operation, CalEEMod for building construction and gas vehicle, BEAM for electric vehicles and SAM for building–integrated photovoltaics. It distinguishes from other cross-sectoral model such as CalEEMod or BEST in that it uses physical models, rather than empirical models, for all sectors, which allows for a more accurate and customizable quantification. It is relevant for short-term multi-sectoral decision making by developers and city planners and long-term policy making by municipal and state officials.
\r\n\r\nFor more information: https://www.osti.gov/biblio/1809220-decision-support-emissions-prediction-interactive-cities-tool
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Predicts the cross-sectoral energy consumption and greenhouse gases emissions at urban scale"},"id":42465485,"isFeatured":false,"isHero":false,"name":"DEPICT - Decision-Support and Emissions Prediction Interactive Cities Tool","path":"energy-efficiency/energy","pcode":"DEPICT"},"-Ni0I1JtXTJ02dXrz6wK":{"description":{"long":"The Distributed Energy Resources Customer Adoption Model (DER-CAM) is a powerful and comprehensive decision support tool for finding optimal distributed energy resource (DER) investments in buildings or multi-energy microgrids.
\r\n\r\nTechnically mature and extensively peer-reviewed, DER-CAM has been developed by researchers at Lawrence Berkeley National Laboratory (Berkeley Lab) since 2000, and can be used to find the optimal portfolio, sizing, placement, and dispatch of a wide range of DER, while co-optimizing multiple stacked value streams that include load shifting, peak shaving, power export agreements, or participation in ancillary service markets.
\r\n\r\nWhile the objective function of DER-CAM can be easily modified — or even replaced by a multi-objective analysis — it is most commonly defined as a site's total annual cost of energy supply. This includes costs associated with both new and existing DER, operation and maintenance costs, fuel costs, and also all costs related to utility imports either fixed, time-dependent, energy-based, or power-based. Additionally, all value streams associated with the optimal DER dispatch determined by DER-CAM are considered in the objective function, both in the form of avoided costs and market participation.
\r\n\r\nFor a more in-depth review on different revenue streams associated with microgrid deployment we suggest the paper found on eta.lbl.gov/publications/value-streams-microgrids-literature.
\r\n\r\nFor more information and to access web based system: https://gridintegration.lbl.gov/der-cam
\r\n\r\nFree as web-based service; Source code available for commercial use $15,000
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"A decision support tool for finding optimal distributed energy resource (DER) investments in buildings or multi-energy microgrids"},"id":42465490,"isFeatured":false,"isHero":false,"name":"DER-CAM - Distributed Energy Resources Customer Adoption Model, Investment and Planning Version","path":"energy-efficiency/energy","pcode":"DER-CAM"},"-Ni0IJP_AlvzB-8EIRE3":{"description":{"long":"IBCheck is a utility that can help data centers, especially large high performance supercomputing centers, to manage and troubleshoot Infiniband related issues.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Management of data center Infiniband issues"},"id":42465445,"isFeatured":false,"isHero":false,"name":"IBCheck","path":"computing/computing-networking-and-data-management","pcode":"IBCheck"},"-Ni0IRSGXrNhKRoYvITh":{"description":{"long":"This software implements the fast, self-consistent probability density estimation described by O'Brien et al. (2014, doi: ). It uses a non-uniform fast Fourier transform technique to reduce the computational cost of an objective and self-consistent kernel density estimation method.
\r\n\r\nFor more information: https://github.com/LBL-EESA/fastkde
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Probability density estimation"},"id":42465455,"isFeatured":false,"isHero":false,"name":"FastKDE - Kernel Density Estimation","path":"computing/computing-networking-and-data-management","pcode":"FastKDE"},"-Ni0IfHIzQ6OEhuXCzoE":{"description":{"long":"This software is a modular detection tool intended to support for monitoring network logs in order to detect denial of service attacks on "research and education" networks that disambiguates such attacks from sustained, high-volume network flows characteristic of large science projects, and referred to as "elephant flows."
\r\n\r\nThis tool currently monitors a directory for nfcapd files. Given an nfcapd directory, this tool will continuously check for newly added log files and apply each analytics module in a separate thread. For example, one thread can calculate the entropy scores for each observed flow, while another thread monitors the number of DNS responses.
\r\n\r\nUsage: detection_main.py -i netflow_directory -o log_name
\r\n\r\nMain module: detection_main.py
\r\n\r\nThe individual detection tests are defined as classes within python modules. The config.ini file determines which tests will be loaded. To add a new test, do the following:
\r\n\r\nDefine the detection test as a class.
\r\n\r\nIn the class, create a function called run_test which takes an nfdump file as input. The start_test() function in detection_tests.py calls this.
\r\n\r\nThen you can add it to the config.ini file by adding "test_name = module_name.class_name"
\r\n\r\nThe tester class also needs a variable called "log_entry". When tester.log_entry is not empty, the entry is recorded to the log by the function feeding nfdump files to the tester.
\r\n\r\nVariables such as test thresholds can be modified using config.ini
\r\n\r\nconfig.ini contains variables for setting test parameters and which tests to run. The variables are loaded into the global dictionary test_vars.
\r\n\r\nFor questions, please contact Sean Peisert sppeisert@lbl.gov. For more information: https://github.com/lbnl-cybersecurity/ddos-detection
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Detection of denial of service attacks on research and education networks"},"id":42465450,"isFeatured":false,"isHero":false,"name":"LBNL-DDoS Detection on Science Networks","path":"computing/computing-networking-and-data-management","pcode":"LBNL_DDoS"},"-Ni0IrsLe1H4nM-6h6QZ":{"description":{"long":"An online self-service portal for testing measurement and verification (M&V) methods/tools using buildings' interval meter data. After registering as a user in the portal, that user can download test data files, run those test data files through their own M&V software, and then upload software modeling results to the online portal as a csv file. After the user has uploaded their modeling results the portal will develop statistical accuracy metrics for that M&V tool. The online portal will summarize test results for some or all of the submitted tests. This online portal has been developed by LBNL, and we have been collaborating with the Efficiency Valuation Organization (EVO) with the objective of EVO managing the portal as an ongoing service. Portal is currently posted at http://mvportal.evo-world.org/
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Portal for testing measurement and verification methods/tools with building interval meter data"},"id":42465500,"isFeatured":false,"isHero":false,"name":"M&V Tool Testing Portal v1","path":"energy-efficiency/energy","pcode":"M-V_Tool_Testing_v1"},"-Ni0JD_JtPbG5A4LWwkG":{"description":{"long":"The MURS-MEGA software employs a Maximum Likelihood Expectation-Maximization (ML-EM) method to estimate the isotope-specific spatial distribution of gamma radioactivity surrounding a mobile radiation detection system in real-time, returning a geo-referenced gamma-ray image. MURS-MEGA was specifically developed for the Mobile Urban Radiation Search (MURS) detection system but may be extensible to other mobile detection platforms.
\r\n\r\nFor more information: https://www.researchgate.net/publication/327876011_Simulation_and_validation_of_the_Mobile_Urban_Radiation_Search_MURS_gamma-ray_detector_response
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Real-time estimation of isotope-specific spatial distribution of gamma radioactivity"},"id":42465505,"isFeatured":false,"isHero":false,"name":"MURS-MEGA Mobile Estimation of Gamma Activity","path":"imaging/sensors-and-detectors","pcode":"MURS-MEGA"},"-Ni0JN9FXOucQVqJCrgL":{"description":{"long":"PARADISE will enable the research community to rapidly evaluate the impact of emerging technologies at the architectural level, and thus provide the means to select among available technologies to facilitate continued digital computing performance scaling.
\r\n\r\nhttps://www.osti.gov/biblio/1785309
\r\n\r\n"
\r\n\r\nA suite of build-optimization software tools (BOOST) to streamline the design-build transition in synthetic biology engineering workflows. The BOOST library offers a wide range of capabilities, including:
\r\n\r\nIn addition, by optimizing the design of DNA sequences, the BOOST library can significantly reduce the cost and turnaround time of DNA synthesis, compared to commercial DNA design software tools.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"PostMoore Architecture and Accelerator Design Space Exploration using Device Level Experiments"},"id":42465385,"isFeatured":false,"isHero":false,"name":"PARADISE","path":"materials/advanced-materials","pcode":"PARADISE"},"-Ni0JRB5U-xpHtvFklQr":{"description":{"long":"A computer program that uses data from single-photon emission computed tomography (SPECT) to quantify and create images of dynamic blood flow in living tissue. This tool will improve noninvasive diagnosis and assessment of diseases using SPECT scanners, which are more common and less expensive than positron emission tomography (PET) scanners. The software generates system matrices that use SPECT data to provide accurate arterial input functions— mathematical functions describing the flow of blood into tissue over time. These functions can be used to quantify regional tissue perfusion and viability, as well as coronary flow reserve. The software can also be applied directly to PET data for cases when these scans are available.
\r\n\r\nThe scientists tested the system by applying it to data from three patients who underwent PET scans of the heart. These data were used to simulate projection data that would be obtained from the same patients with a slowly rotating double-headed SPECT scanner. The simulated SPECT data was then processed with both existing software, which uses a standard three-dimensional (3D) technique at multiple time points, and the new software, which uses a spatiotemporal (4D) technique. The results from each type of software were compared to the original PET results as an indicator of accuracy. The 4D technique was more accurate than the 3D technique in measuring arterial input functions. The 4D program also produced accurate time-activity curves for blood and myocardium and used these to estimate the tissue uptake rate parameter, K1. In addition, the software was able to compensate for errors introduced by radiotracer signal attenuation, collimation-induced blurring, and changes in radiotracer distribution during camera rotation.
\r\n\r\nDynamic imaging of tissue to visualize and quantify blood flow and regional metabolic rates is useful in assessing cardiac and other diseases, as well as normal physiology. While this type of imaging can be performed with PET scanners, these scanners are rare, expensive, require a nearby cyclotron or generator, and can only image one type of isotope at a time. MRI images may also be useful but not all patients can undergo MRI scans. SPECT scanners are more common, convenient, and less expensive than PET scanners and more readily tolerated than MRI scans. However, SPECT scanners have limited capability for dynamic imaging, because, unlike PET scanners, their cameras must rotate slowly about the body as the radiotracer distribution changes. The Berkeley Lab software overcomes these limitations, allowing the more accessible SPECT scanners to provide objective, quantitative data for diagnosis and research.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Software for dynamic imaging"},"id":42465415,"isFeatured":false,"isHero":false,"name":"SPECT Generating Dynamic System Matrices for Dynamic","path":"biosciences/biological-sciences-research-tools-and-methods","pcode":"SPECT"},"-Ni0Jc9spbi5NUUbzROn":{"description":{"long":"A biological computer-aided manufacturing (bioCAM) platform that manages the complexity of synthetic biology workflows and tracks the production of synthetic DNA constructs to maximize efficiency.
\r\n\r\nSynTrack is integrated with laboratory automation systems by enabling task-based workflows to offer complete DNA construct management, assembly pipeline control, and plate and well content capturing. Functions include:
\r\n\r\nOpenPET is a modular, extendible, and high-performance electronics platform suitable for multichannel data acquisition. Due to the flexibility of the architecture, the platform is capable of interfacing with a wide variety of detector modules including medical imaging, homeland security applications, and others.
\r\n\r\nThe analog signals from radiation detectors share similar characteristics – a pulse whose area is proportional to the deposited energy and whose leading edge is used to extract a timing signal. Thus, this allows for a general design of the electronics system. The analog front-end is hosted on a module called a Detector Board, where each board can filter, combine, timestamp, and process multiple channels independently. The analog signal is sampled with a high-speed analog-to-digital converter (ADC), which is processed by an FPGA to extract pulse height information. A leading edge discriminator generates a timing signal that is processed by a time-to-digital converter (TDC) implemented inside the FPGA.
\r\n\r\nThe processed data is formatted and sent through a backplane to a module called Support Board, where one Support Board can host up to eight Detector Board modules. The data in the Support Board, coming from eight Detector Board modules, can be aggregated or correlated (if needed) depending on the algorithm implemented then sent out to a Computer Workstation for further processing.
\r\n\r\nThe number of channels (detector modules) to be processed mandates the overall OpenPET system configuration, which is designed to handle up to 2,048 channels using a 32-channel Detector Board in the standard configuration. Abstract OpenPET offers three system configurations: Small System which is capable of capturing and processing up to 256 analog channels; Standard System, up to 2,048 analog channels; and Large System up to 16,384 analog channels.
\r\n\r\nFOR MORE INFORMATION:
\r\n\r\nOpenPET website: http://openpet.lbl.gov/
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"OpenPET Readout Electronics for Radionuclide Imaging"},"id":42465435,"isFeatured":false,"isHero":false,"name":"OpenPET Hardware, Firmware, Software, and BoardDesign Files","path":"computing/computing-networking-and-data-management","pcode":"OpenPET"},"-NkCI0c7Nc4HVn5MMWVZ":{"description":{"long":"Web application for management, storage, visualization, and statistical analysis of of Mass Spectrometry Imaging (MSI) data.
\r\n\r\nSoftware use Terms and Condition are on the repository site you will be directed to. If you cannot accept please do not install.
\r\n\r\n\r\n
eProject Builder enables Energy Services Companies (ESCOs) and their contracting agencies to:
\r\n1. upload and track project-level Information
\r\n2. generate basic project reports required by local, state, and/or federal agencies
\r\n3. benchmark new Energy Savings Performance Contract (ESPC) projects against historical data
\r\n
Handling large streaming data is essential for various applications such as network traffic analysis, social networks, energy cost trends, and environment modeling. However, it is in general intractable to store, compute, search, and retrieve large streaming data. This software addresses a fundamental issue, which is to reduce the size of large streaming data and still obtain accurate statistical analysis. As an example, when a high-speed network such as 100 Gbps network is monitored, the collected measurement data rapidly grows so that polynomial time algorithms (e.g., Gaussian processes) become intractable.
\r\n\r\nThis software uses a dynamic sampling algorithm, based on the recent technology from the relational dynamic bayesian online locally exchangeable measures, that reduces the storage of data records in a large scale, and still provides accurate analysis of large streaming data. The software can be used for both online and offline data records.
\r\nTool for selecting facility sites for new construction or expansion of existing organic waste-to-energy activities. For evaluation of bioenergy feedstock options for a specific existing site. The web tool displays the following types of data:
\r\n\r\nUsers can interact with the map in the following ways:
\r\n\r\nThe outputs of the algorithmic process are going to appear on the screen after the computation is done. The outputs consist of the locations of all available biomass that are within the buffer zone from the clicked location. By clicking on any point the user can get more information on the nature and amounts of the biomass.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"For site selection for construction or expansion of waste-to-energy activities"},"id":42465410,"isFeatured":false,"isHero":false,"name":"Biositing Webtool","path":"biosciences/biological-sciences-research-tools-and-methods","pcode":"Biositing"},"-NkWXJCJFmgtAMT3XU5d":{"description":{"long":"A tool that uses machine learning to make further advancements in the field of synthetic biology. The patent-pending Automated Recommendation Tool (ART) uses probabilistic modeling techniques to guide metabolic engineering systematically without requiring a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. ART is built around a unique uncertainty quantification approach and has been demonstrated to have high predictive accuracy. Using ART improved tryptophan titer and productivity by up to 74% and 43%, respectively, compared to the best designs used for algorithm training.
\r\n\r\nSmall Business = Companies with 50 or less full-time or part-time employees.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"A machine learning automatied recommendation tool for guiding synthetic biology"},"id":43066425,"isFeatured":false,"isHero":false,"name":"ART (Small Business)","path":"biosciences/biological-sciences-research-tools-and-methods","pcode":"ART_COPY1"},"-NyW3t9vNnpBxjwsaPzi":{"description":{"long":"geNomad is an annotation and classification framework that combines and builds on two standard techniques for identifying viruses and plasmids. Until now, most other tools have focused on identifying only specific plasmids or viruses. geNomad combines a broad scope, targeting all known groups of viruses and plasmids. It is also optimized for speed, i.e., it can identify millions of new viruses and plasmids quickly, even in massive datasets.
\r\n\r\ngeNomad employs two distinct approaches to identify both viruses and plasmids; one is marker gene-based, and the second is a neural network approach. The tool was employed to build version 4 of the JGI’s IMG Virus Resource (IMG/VR), now with more than 15 million viral genomes. It was also key to developing the first version of the IMG Plasmid Resource (IMG/PR), which currently has more than 700,000 plasmids from genomes, metagenomes and metatranscriptomes.
\r\n\r\nFor more information: https://jgi.doe.gov/scihi-genomad/
\r\n\r\nPublication: Camargo, A.P., et al. “Identification of mobile genetic elements with geNomad.” Nature Biotechnology. 21 September 2023. doi: 10.1038/s41587-023-01953-y
\r\n\r\nFor the full text of each license type go here.
\r\n","short":"Identifies and classifies viruses and plasmids"},"id":45171555,"isFeatured":false,"isHero":false,"name":"GeNomad","path":"biosciences/human-health-and-precision-medicine","pcode":"GeNomad"},"-NyW3xFOhpFqtUoyU8hk":{"description":{"long":"SALSA is a semi-analytical modeling tool that can provide assessments of pressure perturbations and brine leakage because of fluid injection and extraction activities in sedimentary basins. SALSA is the first to account for the coupled leakage through aquitards and leaky wells, with geologic pressurization sources. This comprehensive approach enables a more accurate representation of real-world scenarios, enhancing the reliability of predictions.
\r\n\r\nSALSA utilizes semi-analytical solutions, making it computationally efficient for problems involving multiple injection and leaky wells in multilayered sedimentary systems. It avoids the need for computationally intensive local mesh refinement around each well, which is often required by numerical simulation software for accurate results. Therefore, stakeholders (e.g., regulators, operators) for site screening, injection and post-injection pressure behavior and assessing leakage risks can use SALSA as a fast-predictive tool in GCS applications in multilayered aquifer systems.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n","short":"Assessment of pressure perturbations and brine leakage in sedimentary basins for geologic carbon sequestration"},"id":45172270,"isFeatured":false,"isHero":false,"name":"SALSA - Semi-Analytical Leakage Solutions for Aquifers","path":"geoenvironment/water-and-the-environment","pcode":"SALSA"},"-NyW4-OGSMvXL2uan5Xl":{"description":{"long":"MESHMAKER V2.0 is a code that describes the system geometry and discretizes the domain in problems of flow and transport through porous and fractured media that are simulated using the TOUGH+], TOUGH2 or TOUGH3 families of codes.
\r\n\r\nMESHMAKER V2.0 is an upgrade from the MESHMAKER V1.5 and the improvements focus on the simplification of the data inputs and on the enhancement of gridding options and capabilities in fractured media. The code is a stand-alone product written in FORTRAN 95/2003, and can be run on any computational platform (workstations, PC, Macintosh).
\r\n\r\nYou must have purchased a TOUGH product to use Meshmaker.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n\r\nFor technical questions, please contact the TOUGH developers.
\r\n","short":"MESHMAKER V2.0 is a code that describes the system geometry and discretizes the domain in problems of flow and transport through porous and fractured media."},"id":44750900,"isFeatured":false,"isHero":false,"name":"MeshMaker v.2 (Source)","path":"tough/tough-ancillary-codes","pcode":"MeshMaker"},"-O5TsE3DTvjGN18R_wlc":{"description":{"long":"Bore II provides information for solving water quality and supply problems and for improving remediation of contaminated sites. Termed “hydrophysical logging,” this technology is based on a new concept for measuring fluid flow that enables characterization of groundwater problems more quickly, more cost effectively, and with higher resolution than ever before.
\r\n\r\nCombining Bore II with advanced downhole instrumentation (the hydrophysical logging tool), the method quantifies inflow and outflow locations, their associated flow rates, and the basic water quality parameters of the associated formation waters (e.g., pH, oxidation-reduction potential, temperature). In addition, when applied in conjunction with downhole fluid sampling, Bore II makes possible a complete assessment of contaminant concentration within groundwater. Bore II only runs on Windows operating system.
\r\n\r\nAdditional links and information:
\r\nTechnical description of hydrophysical logging
\r\nExample: Field Data
\r\nExample: Field Schedule
For the full text of each license type and definitions go here.
\r\n","short":"Characterization of groundwater problems, for solving water quality and supply problems and remediation of contaminated sites"},"id":46895281,"isFeatured":false,"isHero":false,"name":"BORE II","path":"geoenvironment/water-and-the-environment","pcode":"BOREII"},"-ODqYf9B4nRsxONwLSqg":{"description":{"long":"This software is a set of analytics that monitor both power measurements collected by distribution grid phasor measurement units (µPMUs) and SCADA communication in order to detect cyber attacks against equipment located in distribution grid substations. It leverages both the Zeek (née Bro) Network Security Monitor and the LBNL Stream-Processing Architecture for Real-time Cyber-physical Security (SPARCS). This software is available free of charge for research and development, non-commercial use. A commercial use license is available from Berkeley Lab. Please contact Berkeley Lab’s Intellectual Property Office at ipo@lbl.gov for more information.
\r\n\r\nFor more information: https://secpriv.lbl.gov//project/powerdata/
\r\n\r\nFor other cybersecurity software: https://secpriv.lbl.gov/software/
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n\r\n","short":"Detection of cyber attacks against equipment located in distribution grid substations"},"id":42465440,"isFeatured":false,"isHero":false,"name":"Analytic-SPARCS - Analytics for Stream-Processing Architecture for Real-time Cyber-physical Security","path":"computing/computing-networking-and-data-management","pcode":"Analytic-SPARCS"},"-OSygARHo6o8iKwhA-3S":{"description":{"long":"SPECTRE-ML is a machine learning-based software for finding optimal clusters of radiation detector segments (pixels/voxels) to enhance spectroscopic performance of detectors. By learning detector-specific trends—such as dead layers, edge effects, and gain shifts—it outperforms traditional methods like uniform depth clustering. The platform streamlines the entire workflow, from data preprocessing and ML algorithm execution to output evaluation and visualization. Designed for highly-segmented CdZnTe (CZT) detectors in International Atomic Energy Agency (IAEA) non-destructive assay safeguards tasks, SPECTRE-ML ensures precise nuclear material verification. Its adaptable framework also supports extension to other segmented detectors, making it a versatile tool for next-generation radiation spectroscopy.
\r\n\r\nFor pricing, contact ipo@lbl.gov
\r\n","short":"SPECTRE-ML: Spectral Peak Enhancement via Machine Learning"},"id":50591226,"isFeatured":false,"isHero":false,"name":"SPECTRE-ML: Spectral Peak Enhancement via Machine Learning","path":"computing/computing-networking-and-data-management","pcode":"SPECTRE","purchaseByQuote":true},"-OYlkBbqE7yeMUmv54Es":{"description":{"long":"The BioC2G tool includes a Python-based model for running techno economic analyses and life-cycle assessments of biofuel and bioproduct production pathways as well as an easy-to-use web interface.
\r\n
\r\nModels for the following pathways are currently built into the tool: limonene, limonane, bisabolene, bisabolane, ethanol, isoprenol, DMCO, HEFA, and alcohol-to-jet. Additionally, a "Custom" option is available for analyzing a bioproduction pathway not included among the built-in examples. Users must supply key product properties and process parameters.
\r\n
\r\nThree types of model runs are available in the tool: minimum selling price (MSP), water consumption, and greenhouse gas (GHG) emissions. Running the MSP model yields a breakdown of MSP by major process stage of production, along with a table of estimated capital expenditures (CAPEX) and annual operating expenditures (OPEX). Running the water consumption and GHG models yields a breakdown of water consumed and carbon emissions respectively, per unit of end product. A breakdown of these metrics by major process stage is also provided. Model run results can be viewed in the web interface numerically and graphically, as well as downloaded in CSV format. Detailed documentation on model methodology and assumptions is also available for download.
Large Business = Companies with over 50 full-time or part-time employees.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n\r\nNon-Profit organizations, select Commercial license.
\r\n","short":"The BioC2G tool includes a Python-based model for running techno economic analyses and life-cycle assessments of biofuel and bioproduct production pathways as well as an easy-to-use web interface."},"id":51361776,"isFeatured":false,"isHero":false,"name":"BioC2G (Large Business)","path":"biosciences/jbei","pcode":"BC2GL","purchaseByQuote":false},"-OYlkHKQz2mOVgmSJegj":{"description":{"long":"The BioC2G tool includes a Python-based model for running techno economic analyses and life-cycle assessments of biofuel and bioproduct production pathways as well as an easy-to-use web interface.
\r\n
\r\nModels for the following pathways are currently built into the tool: limonene, limonane, bisabolene, bisabolane, ethanol, isoprenol, DMCO, HEFA, and alcohol-to-jet. Additionally, a "Custom" option is available for analyzing a bioproduction pathway not included among the built-in examples. Users must supply key product properties and process parameters.
\r\n
\r\nThree types of model runs are available in the tool: minimum selling price (MSP), water consumption, and greenhouse gas (GHG) emissions. Running the MSP model yields a breakdown of MSP by major process stage of production, along with a table of estimated capital expenditures (CAPEX) and annual operating expenditures (OPEX). Running the water consumption and GHG models yields a breakdown of water consumed and carbon emissions respectively, per unit of end product. A breakdown of these metrics by major process stage is also provided. Model run results can be viewed in the web interface numerically and graphically, as well as downloaded in CSV format. Detailed documentation on model methodology and assumptions is also available for download.
Small Business = Companies with fewer than 50 full-time or part-time employees.
\r\n\r\nFor the full text of each license type and definitions go here.
\r\n\r\nNon-Profit organizations, select Commercial license.
\r\n","short":"The BioC2G tool includes a Python-based model for running techno economic analyses and life-cycle assessments of biofuel and bioproduct production pathways as well as an easy-to-use web interface."},"id":51424703,"isFeatured":false,"isHero":false,"name":"BioC2G (Small Business)","path":"biosciences/jbei","pcode":"BC2GS","purchaseByQuote":false},"-OnIFAboZS79r1_aODsW":{"description":{"long":"The Interruption Cost Estimate (ICE) Calculator is a tool designed for electric reliability planners at utilities, government organizations or other entities that are interested in estimating interruption costs and/or the benefits associated with reliability improvements.
\r\n\r\nThis executable zip file contains two spreadsheets that allow users to use the tool offline: (1) ICE 2-Estimate_Interruption_Costs_v2.2.0 02132026.xlsm and (2) ICE 2-Value_of_Reliability_Improvement_v2.2.0 04092026.xlsm. In addition, these spreadsheets contain the ICE Calculator's explanatory variables--and their coefficients--which are used to calculate the interruption costs and value of reliability improvements. These equations--known as Customer Damage Functions (CDFs)--can be embedded into third-party software or used for other internal planning purposes as long as the underlying CDFs are not shared outside of the licensed organization.
\r\n\r\nThe tool was developed by Lawrence Berkeley National Laboratory (LBNL) and Resource Innovations, Inc.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n\r\n","short":"A reliability planning tool for electric utilities"},"id":53074686,"image":"https://static.avangate.net/images/merchant/cb1d78edc3b427d8f919a169d6931636/products/FINAL%20ICE%202%20RGB-01.jpg","isFeatured":false,"isHero":false,"name":"ICE Calculator","path":"energy-efficiency/energy","pcode":"ICE","purchaseByQuote":false},"-Os2IHUt796hkVsutm5Z":{"description":{"long":"Distributed Acoustic Sensing (PESO-DAS), a software platform that automates the processing of continuous seismic data acquired from Distributed Acoustic Sensing (DAS) fiber-optic systems and permanent seismic sources, such as the Surface Orbital Vibrators (SOVs). This tool generates processed shot gathers and quality control plots, enabling real-time time-lapse (4D) seismic monitoring. It supports long-term subsurface surveillance for applications like geological carbon storage, geothermal reservoirs, and oil and gas fields. Its use can allow, for example, daily snapshots of CO2 plume evolution during carbon storage or hourly snapshot of fracture growth during hydraulic fracturing.
\r\n\r\nThis technology is differentiated by streamlining the complex workflow of continuous seismic monitoring, specifically integrating DAS and SOVs for advanced subsurface imaging. Its automation capabilities provide a robust solution for long-term, high-resolution surveillance, crucial for dynamic environments. The software’s specialized design for this combined sensing approach offers a unique advantage in managing and interpreting fiber-optics datasets for critical resource management. Developed in Matlab for Windows, it uses proprietary code.
\r\n\r\nFor the full text of each license type go here.
\r\n\r\n\r\n","short":"Distributed Acoustic Sensing (PESO-DAS) software automates continuous seismic data processing from fiber-optic sensors and permanent seismic sources"},"id":53621336,"isFeatured":false,"isHero":false,"name":"PESO-DAS","path":"geoenvironment/water-and-the-environment","pcode":"PESO_DAS","purchaseByQuote":false}},"releases":{"-LANJLbaVlSrXKAffQUb":{"newData":"{\"categories\":{\"children\":{\"-KwZG1PjJbkQfELZnvjk\":{\"active\":true,\"children\":{\"-KwqP4RUJT7p22cRcLNI\":{\"active\":true,\"name\":\"Sensors and Detectors\",\"slug\":\"sensors-and-detectors\"},\"-KxyFvg_5NFh1KAm1BGN\":{\"active\":true,\"name\":\"Spectroscopy and Microscopy\",\"slug\":\"spectroscopy-and-microscopy\"},\"-KxyFydgmstjGzOysPNG\":{\"active\":true,\"name\":\"Lasers and Particle Accelerators\",\"slug\":\"lasers-and-particle-accelerators\"},\"-KxyG0ShlfEdK4d-4e3E\":{\"active\":true,\"name\":\"Imaging - Medical\",\"slug\":\"imaging-medical\"}},\"name\":\"Imaging\",\"slug\":\"imaging\"},\"-KwZG3MiB51bFk4uOXLl\":{\"active\":true,\"children\":{\"-KwZwGL0yJCI8XYDLQKj\":{\"active\":true,\"name\":\"Semiconductors and Photonics\",\"slug\":\"semiconductors-and-photonics\"},\"-KwZwJg2bHw4IkByjjEZ\":{\"active\":true,\"name\":\"Advanced Materials\",\"slug\":\"advanced-materials\"}},\"name\":\"Materials\",\"slug\":\"materials\"},\"-KwZH4VaI2bUFBuaDEFn\":{\"active\":true,\"children\":{\"-KwZwalcmSZ6IYoQQuYq\":{\"active\":true,\"name\":\"Energy Generation and Storage\",\"slug\":\"energy-generation-and-storage\"},\"-KwZwcPnqJ0QM8iShkLj\":{\"active\":true,\"name\":\"Building Energy and Analysis\",\"slug\":\"building-energy-and-analysis\"}},\"name\":\"Energy / Buildings\",\"slug\":\"energy-buildings\"},\"-KwZH6wZVuZncxsMXZU7\":{\"active\":true,\"children\":{\"-KwZwfMyAZWXy765uiIM\":{\"active\":true,\"name\":\"Computing, Networking and Data Management\",\"slug\":\"computing-networking-and-data-management\"}},\"name\":\"Computing\",\"slug\":\"computing\"},\"-KwZwkT0HFKhsR7gCK0Q\":{\"active\":true,\"children\":{\"-KwZwnCGPmvWEr7Efovg\":{\"active\":true,\"children\":{\"-KxyGMMGhN5Vxz44Oio_\":{\"active\":true,\"name\":\"Geophysics and Flows\",\"slug\":\"geophysics-and-flows\"}},\"name\":\"Water and the Environment\",\"slug\":\"water-and-the-environment\"}},\"name\":\"Geo/Environment\",\"slug\":\"geoenvironment\"},\"-KwqBajlemlrQc-HxuN1\":{\"active\":true,\"children\":{\"-KwqBmyGpfEOmEfhT1m7\":{\"active\":true,\"name\":\"Biobased Fuels and Chemicals\",\"slug\":\"biobased-fuels-and-chemicals\"},\"-KwqBpmzBjQ0sCAP-XET\":{\"active\":true,\"name\":\"Synthetic Biology\",\"slug\":\"synthetic-biology\"},\"-KwqBrV6yXRUaaXfYa4K\":{\"active\":true,\"name\":\"Human Health and Precision Medicine\",\"slug\":\"human-health-and-precision-medicine\"},\"-KwqBtEcUqjPbUBdANoB\":{\"active\":true,\"name\":\"Computational Biology\",\"slug\":\"computational-biology\"},\"-KwqBualmp-yLgwLMoRL\":{\"active\":true,\"name\":\"Microbiome Research\",\"slug\":\"microbiome-research\"},\"-KwqBwJZdbQNyu3z_OxU\":{\"active\":true,\"name\":\"Biological Sciences Research Tools and Methods\",\"slug\":\"biological-sciences-research-tools-and-methods\"},\"-KwqBxbSGKDi7o1yYIWY\":{\"active\":true,\"name\":\"Imaging - Medical\",\"slug\":\"imaging-medical\"}},\"name\":\"Biosciences\",\"slug\":\"biosciences\"},\"-KwqBcfDuqF89ud8SSzB\":{\"active\":true,\"children\":{\"-KxyGYllZVqslM9zYyZp\":{\"active\":true,\"children\":{\"-KxyGbhnvD-9HG-jXE1O\":{\"active\":true,\"name\":\"Tough\",\"slug\":\"tough\"}},\"name\":\"TOUGH+\",\"slug\":\"tough+\"},\"-L5F2CKe_BlZU7hQDmSG\":{\"active\":true,\"name\":\"TOUGH3\",\"slug\":\"tough-3\"},\"-L5Ib5ahwFXDbCaeQ035\":{\"active\":true,\"name\":\"TOUGHREACT\",\"slug\":\"toughreact\"},\"-L5Ib8gigGLxJSDHEvaO\":{\"active\":true,\"name\":\"iTOUGH2\",\"slug\":\"itough2\"},\"-L5IbFXM7UE8hvgYICB9\":{\"active\":true,\"name\":\"TOUGH Ancillary codes\",\"slug\":\"tough-ancillary-codes\"}},\"name\":\"TOUGH\",\"slug\":\"tough\"}},\"name\":\"Categories\"},\"products\":{\"-L3dFRnJtHf9wW2myWTj\":{\"isFeatured\":true,\"isHero\":false,\"path\":\"geoenvironment/water-and-the-environment\",\"pcode\":\"geot_standard_2-1\",\"searchInfo\":\"geot standard\"},\"-L3dFjhrDgwLTPA9qtGa\":{\"isFeatured\":false,\"isHero\":false,\"path\":\"tough/tough+\",\"pcode\":\"toughplus_hydrate_executable\",\"searchInfo\":\"TOUGH+: solves mass and energy balance equations that describe fluid and heat flow in general multiphase, multicomponent, porous-media systems\\tTOUGH+, a re-engineered, modular design of TOUGH2, offers new capabilities including an extended range for the thermodynamic properties of water to include ice. 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