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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

IDC reengineering Phase 2 & 3 US industry standard cost estimate summary

Sandia National Laboratories has prepared a ROM cost estimate for budgetary planning for the IDC Reengineering Phase 2 & 3 effort, using a commercial software cost estimation tool calibrated to US industry performance parameters. This is not a cost estimate for Sandia to perform the project. This report provides the ROM cost estimate and describes the methodology, assumptions, and cost model details used to create the ROM cost estimate. ROM Cost Estimate Disclaimer Contained herein is a Rough Order of Magnitude (ROM) cost estimate that has been provided to enable initial planning for this proposed project. This ROM cost estimate is submitted to facilitate informal discussions in relation to this project and is NOT intended to commit Sandia National Laboratories (Sandia) or its resources. Furthermore, as a Federally Funded Research and Development Center (FFRDC), Sandia must be compliant with the Anti-Deficiency Act and operate on a full-cost recovery basis. Therefore, while Sandia, in conjunction with the Sponsor, will use best judgment to execute work and to address the highest risks and most important issues in order to effectively manage within cost constraints, this ROM estimate and any subsequent approved cost estimates are on a 'full-cost recovery' basis. Thus, work can neither commence nor continue unless adequate funding has been accepted and certified by DOE.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Deliverable 6.7-Final Technical Report: Development Summary and Evaluation of the Solar Uncertainty Integrator (SUNI) Software

The Data Quality and Uncertainty Integration Project was a three-year effort to address stakeholder needs for assessing solar radiation resource data quality based on existing tools for estimating radiometer measurement uncertainties and assessing post-measurement data quality. The annual research objectives for the project addressed a logical progression of effort needed to achieve the ultimate project goal of developing the Solar Uncertainty Integrator (SUNI) software. This final technical report summarizes the development process for achieving these key research objectives and addresses the outreach and code development efforts in the final year of the project to develop a new solar irradiance data uncertainty integration software package.

14 SOLAR ENERGY↗
DOE OSTI2023

Risk Analysis of Various Design Architectures for High Safety-significant Safety-related Digital Instrumentation and Control Systems of Nuclear Power Plants during Accident Scenarios

This report documents the plus-up activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2022 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades/designs. An integrated risk assessment technology for the DI&C systems was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the safety margin obtained from plant modernization, especially for the high safety-significant safety-related (HSSSR) DI&C systems, (2) support and supplement existing advanced risk-informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems to support system design decisions and diversity and redundancy applications, (4) assure the long-term safety and reliability of HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals and deal with the expensive licensing justifications from regulatory insights, the LWRS-developed framework instructs nuclear vendors and utilities on how to effectively lower the costs associated with digital compliance and speed industry advances by: (1) defining an integrated risk-informed analysis process for DI&C upgrade, including hazard analysis, reliability analysis, and consequence analysis, (2) applying systematic and risk-informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development, licensing, and deployment of advanced DI&C technologies on nuclear power plant (NPPs). Adding diversity within system or components is the main means to eliminate and mitigate CCFs, but diversity also increases plant complexity and errors and may not address all sources of systematic failures. How to optimize the diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in HSSSR DI&C systems of NPPs and supporting relevant design optimization, the framework provides: ? An integrated best-estimate, risk-informed capability to address new technical digital issues quantitatively, accurately, and efficiently in plan modernization progress, such as software CCFs in HSSSR DI&C systems of NPPs ? A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to efficiently predict and prevent risk in the early design stage of DI&C systems ? Technical bases and risk-informed insights to assist U.S. Nuclear Regulatory Commission (NRC) and industry to address and fulfill the risk-informed alternatives for evaluation of CCFs in HSSSR DI&C systems of NPPs ? An integrated risk-informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The plus-up research and development efforts of this project in FY 2022 are focused on methodology improvement of software CCF modeling and estimation, prevention analysis, importance analysis and risk analysis of various design architectures of HSSSR DI&C systems. This work greatly enhances the capability of the LWRS-developed framework for the risk assessment and design optimization of safety-critical DI&C systems. It should be noted that all the analyses are performed for the demonstration of the LWRS-developed framework, not for the evaluation of relevant systems. Results are obtained based on very limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

An Integrated Framework for Risk Assessment of Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology Refinement and Exploration

This report documents activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2023 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective, and secure DI&C technologies for digital upgrades/designs. A risk assessment-informed framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk informed capability to quantitatively estimate the safety margin obtained from plant modernization, especially for safety-related DI&C systems, (2) support and supplement existing risk informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of safety-related DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the LWRS-developed framework provides a means to address relevant technical issues by: (1) defining a risk informed analysis process for DI&C upgrade that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies in nuclear power plants (NPPs). Adding diversity within a system or components is the primary means to eliminate and mitigate CCFs, but diversity also increases system complexity and may not address all sources of systematic failures. Optimization of diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in safety-related DI&C systems of NPPs and supporting relevant design optimization, the proposed framework provides: (a) A best-estimate, risk informed capability to address new technical digital issues quantitatively, focusing on software CCFs in safety-related DI&C systems of NPPs; (b) A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to predict and prevent risk in the early design stage of DI&C systems; (c) Technical bases and risk informed insights to assist users address the risk informed alternatives for evaluation of CCFs in safety-related DI&C systems of NPPs; and (d) A risk informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The research and development efforts of this project in FY 2023 are focused on refining current methods on software CCF modeling and estimation and exploring additional innovative approaches to risk assessment of DI&C systems to enable a more comprehensive and complete assessment of various safety-related DI&C design architectures. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists. It should be noted that all the analyses are performed for the demonstration of the methodology, not for the evaluation of an actual digital control system. Results are obtained based on limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Software Quality Assurance for EBR-II Fuels Irradiation and Physics Database (FIPD)

The Fuels Irradiation and Physics Database (FIPD) is an ongoing DOE project on archival of the EBR-II metal-alloy fuel irradiation experiments. As part of its use in support of license applications, the Quality Assurance Program Plan (QAPP) was drafted and endorsed by NRC in an effort to demonstrate its compliance with regulatory expectations. Software Quality Assurance (SQA) for the physics portion of FIPD is intended to qualify the calculated quantities such as fuel and cladding temperatures, neutron fluence and axially varying burnup estimates for irradiated fuel elements. This report covers the initial evaluation of SQA status of three neutron physics and thermo-fluid codes (REBUS, RCT and SE2RCT) that form the basis of calculated quantities for as-irradiated characteristics of the tested metallic fuel elements. The report also introduces an SQA plan to address the identified deficiencies. The REBUS, RCT, and SE2RCT codes are all part of the Argonne Reactor Code (ARC) code system. There is considerable knowledge and experience on REBUS and RCT but relatively less on SE2RCT. During FY2021, efforts focused on an assessment of how the data in the EBR-II Physics and Analysis DataBase (PADB) is generated with SE2RCT and used in FIPD. Additional tasks included considerations of uncertainties for power estimates in REBUS and RCT calculations and their impact on the combined RCT methodology. The RCT software usage in FIPD was assessed this year and the input/output details studied. A “requirements” document was created that identifies the key features of the RCT software being used in FIPD that need to have SQA documentation. A brief discussion on the history of RCT and its input is included in this report along with the basic SQA roadmap laid out in the requirements document. The SE2RCT software usage in FIPD is still being studied noting that there is no current manual. As part of the work done this year, two bugs were identified in the SE2RCT software which have a minor impact on the accuracy of the results it produces. No requirements document has been created, but one identified feature of SE2RCT being used that needs verification was its fuel pin temperature calculation. The work completed this year confirms that the approximations which will be included in the software verification report for SE2RCT are accurate. In addition to software quality assurance work for RCT and SE2RCT, an automated verification framework is proposed to simplify the software quality assurance process. The purpose of this framework is to streamline code verification and documentation while minimizing repetitive tasks for code developers and reviewers. The reduction of repeated input (between reference solution, software, and documentation input) throughout the SQA process reduces potential for human errors during the preparation of the supporting software quality records. The automation of the verification and documentation process proposed for this project leverages the existing verification structure already in place for the SAS4A/SASSYS-1 code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

SITCOMTN-154: Initial studies of photometric redshifts with LSSTComCam from DP1

This technote holds reports based on the first analyses of the Data Preview 1 (DP1) data by the Science Unit for photometric redshifts. Although photometric redshifts are not an official DP1 data product, the "Photo-z Science Unit" generated photo-z estimates for every galaxy in DP1 using the available multi-band imaging on a best-effort basis. This work included developing training and test datasets by matching DP1 data to high-quality reference redshifts obtained with spectroscopy, Grism data, and multi-band photometry. The Science Unit used the RAIL software package to make photometric redshift estimates using eight different algorithms, developed simple scientific performance metrics, used those metrics to explore how the performance of the algorithms varied with configuration changes, derived more optimized configurations of the algorithms and tested the performance of those configurations. This work, the resulting data products and expected data distribution mechanism are all described there.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Thermochimica User Manual – v1.0

A new software library called Thermochimica has been developed that determines a unique combination of phases and their compositions at thermochemical equilibrium. The development of Thermochimica in this research is aimed at direct integration in multi-physics codes and to address several concerns with using commercially available software, including: licensing entanglements associated with code distribution, access to the source code, convenient incorporation into other codes with quality assurance considerations, and computational performance. In particular, significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. The overall goal of this undertaking is to provide an open source computational tool to enhance the predictive capability of multiphysics codes without significantly impeding computational performance. The purpose of this document is to describe the design of Thermochimica and the basic use of the software library. A brief background to computational thermodynamics and the conditions for thermodynamic equilibrium is given in §2, details of the code development is discussed in §3, details of building and compiling Thermochimica is given in §4, specific programming details for each subroutine in the library is given in the Appendix. The open license for Thermochimica is provided with the source code. As is always the case, software quality assurance (SQA) is an extremely important subject in software development. The importance of this warrants an independent document dedicated to SQA, which has been developed in parallel to this document. The subject of thermodynamic model validation is also of extreme importance in scientific computing and must be given careful attention. To be clear, this document is concerned with the development and use of a general thermodynamic solver and the validation of any models should be included in the discussion of the development of a thermodynamic model that is specific to a particular system.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Root Cause Correlation Analysis of Software Failures via Orthogonal Defect Classification and Natural Language Processing

Systems theoretic process analysis (STPA) is becoming an increasingly popular technique to assess how complex digital software systems can fail. Rather than defining failures by their observable failure events, which may be sparse especially for safety rated nuclear digital instrumentation and control systems (DI&C), failures are defined as postulated unsafe actions under specific contextual conditions. This permits a top-down analysis of system hazards and identifies whether imposed constraints and requirements can sufficiently address undesirable hazards. However, STPA is a qualitative approach at identifying inadequacies in the development process and cannot currently be used to quantify unsafe action likelihoods for probabilistic risk assessment. Therefore, in this work, we examine the root causes of software failure and explore whether a consistent correlation can be linked to specific unsafe action classes. We implement Lbl2Vec, an unsupervised document classification and retrieval algorithm, on a database of 4,096 software defect reports acquired from various open-source software systems. By analyzing sentence structure, embedded labels, and word vectors, we show that certain defect types positively correlate to specific unsafe action classes over others. The correlations developed can be used to estimate the failure probability of safety intended DI&C systems which provides a licensing basis for nuclear plant modernization efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

The Future of EPA's Waste Estimation Support Tool - 17227

The Environmental Protection Agency's (EPA's) Waste Estimation Support Tool (WEST) is a GIS-based decision support tool for estimating the characteristics, amount, and residual radioactivity of waste generated from remediation and cleanup activities after a radiological incident, including those involving radiological dispersal devices, improvised nuclear devices, and nuclear power plants. WEST has been released to the public and has been used in numerous national level exercises and planning scenarios; however, it continues to be improved and refined to add additional functionality and performance. Since its inception, WEST has undergone a myriad of updates, routinely ensuring compatibility with ESRI's ArcGIS and FEMA's Hazus, a tool for estimating potential losses from earthquakes, wind, and flood events. Furthermore, recent enhancements have added reporting and mapping features and multi-state support. Over time, this progress has strained WEST's Microsoft{sup C} Excel based platform. The inherent limitations of Excel have limited the capacity of WEST and narrowed the scope of potential enhancements. Recent collaborative efforts between the Department of Homeland Security's (DHS's) Science and Technology Directorate (S and T) and EPA will see the introduction of a new software platform for easing memory limitations and new and innovative features for improving the accuracy of waste estimates. The planned enhancements include: 1) Systems approach: measure or predict the outcome of decisions associated with disaster response (e.g., decontamination efficacy vs. waste) and to a greater extent, the overall resource demand (e.g., cost, time, etc.); 2) Custom infrastructure data and international support: accommodate non-US building information where available and also add new data and information on recently used decontamination technologies as applied in a real-world incident; 3) Additional waste factors: addition of waste factors that are unique to wide area scenarios such as vehicles and trees as they will likely contribute in a significant manner to the overall waste stream;4) Site analysis and logistics: apply spatial information and analysis technologies to locate and prioritize potential waste staging or storage sites; and use GIS-based logistics planning to better organize, route, and estimate the cost, time, and logistical requirements (i.e., resource demand) associated with transporting large volumes of waste from a disaster-stricken area to waste staging or storage sites; 5) Decontamination technologies: introduce new decontamination technologies, better understand the feasibility and efficacy of new and preexisting decontamination technologies when applied to a wide area incident, and use historical incidents to ground truth waste results; and 6) Resource demand: ability to estimate resource demand information associated with decontamination technologies, waste staging and storage, and logistical information for transporting waste. This paper will describe the next version of WEST (WEST 4.0), and how the aforementioned enhancements will contribute to improving the planning and response capabilities of the tool. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Root Cause Correlation Analysis of Software Failures via Orthogonal Defect Classification and Natural Language Processing

Systems theoretic process analysis (STPA) is becoming an increasingly popular technique to assess how complex digital software systems can fail. Rather than defining failures by their observable failure events, which may be sparse especially for safety rated nuclear digital instrumentation and control systems (DI&C), failures are defined as postulated unsafe actions under specific contextual conditions. This permits a top-down analysis of system hazards and identifies whether imposed constraints and requirements can sufficiently address undesirable hazards. However, STPA is a qualitative approach at identifying inadequacies in the development process and cannot currently be used to quantify unsafe action likelihoods for probabilistic risk assessment. Therefore, in this work, we examine the root causes of software failure and explore whether a consistent correlation can be linked to specific unsafe action classes. We implement Lbl2Vec, an unsupervised document classification and retrieval algorithm, on a database of 4,096 software defect reports acquired from various open-source software systems. By analyzing sentence structure, embedded labels, and word vectors, we show that certain defect types positively correlate to specific unsafe action classes over others. The correlations developed can be used to estimate the failure probability of safety intended DI&C systems which provides a licensing basis for nuclear plant modernization efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Integrated Cost and Schedule using Monte Carlo Simulation of a CPM Model - 12419

This discussion of the recommended practice (RP) 57R-09 of AACE International defines the integrated analysis of schedule and cost risk to estimate the appropriate level of cost and schedule contingency reserve on projects. The main contribution of this RP is to include the impact of schedule risk on cost risk and hence on the need for cost contingency reserves. Additional benefits include the prioritizing of the risks to cost, some of which are risks to schedule, so that risk mitigation may be conducted in a cost-effective way, scatter diagrams of time-cost pairs for developing joint targets of time and cost, and probabilistic cash flow which shows cash flow at different levels of certainty. Integrating cost and schedule risk into one analysis based on the project schedule loaded with costed resources from the cost estimate provides both: (1) more accurate cost estimates than if the schedule risk were ignored or incorporated only partially, and (2) illustrates the importance of schedule risk to cost risk when the durations of activities using labor-type (time-dependent) resources are risky. Many activities such as detailed engineering, construction or software development are mainly conducted by people who need to be paid even if their work takes longer than scheduled. Level-of-effort resources, such as the project management team, are extreme examples of time-dependent resources, since if the project duration exceeds its planned duration the cost of these resources will increase over their budgeted amount. The integrated cost-schedule risk analysis is based on: - A high quality CPM schedule with logic tight enough so that it will provide the correct dates and critical paths during simulation automatically without manual intervention. - A contingency-free estimate of project costs that is loaded on the activities of the schedule. - Resolves inconsistencies between cost estimate and schedule that often creep into those documents as project execution proceeds. - Good-quality risk data that are usually collected in risk interviews of the project team, management and others knowledgeable in the risk of the project. The risks from the risk register are used as the basis of the risk data in the risk driver method. The risk driver method is based in the fundamental principle that identifiable risks drive overall cost and schedule risk. - A Monte Carlo simulation software program that can simulate schedule risk, burn WM2012 rate risk and time-independent resource risk. The results include the standard histograms and cumulative distributions of possible cost and time results for the project. However, by simulating both cost and time simultaneously we can collect the cost-time pairs of results and hence show the scatter diagram ('football chart') that indicates the joint probability of finishing on time and on budget. Also, we can derive the probabilistic cash flow for comparison with the time-phased project budget. Finally the risks to schedule completion and to cost can be prioritized, say at the P-80 level of confidence, to help focus the risk mitigation efforts. If the cost and schedule estimates including contingency reserves are not acceptable to the project stakeholders the project team should conduct risk mitigation workshops and studies, deciding which risk mitigation actions to take, and re-run the Monte Carlo simulation to determine the possible improvement to the project's objectives. Finally, it is recommended that the contingency reserves of cost and of time, calculated at a level that represents an acceptable degree of certainty and uncertainty for the project stakeholders, be added as a resource-loaded activity to the project schedule for strategic planning purposes. The risk analysis described in this paper is correct only for the current plan, represented by the schedule. The project contingency reserve of time and cost that are the main results of this analysis apply if that plan is to be followed. Of course project managers have the option of re-planning and re-scheduling in the face of new facts, in part by mitigating risk. This analysis identifies the high-priority risks to cost and to schedule, which assist the project manager in planning further risk mitigation. Some project managers reject the results and argue that they cannot possibly be so late or so overrun. Those project managers may be wasting an opportunity to mitigate risk and get a more favorable outcome. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL’s Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Integration, Validation, and Application of a PV Snow Coverage Model in SAM

Due to the increasing deployment of PV systems in snowy climates, there is significant interest in a method capable of estimating PV losses resulting from snow coverage that has been verified for a variety of system designs and locations. Many independent snow coverage models have been developed over the last 15 years; however, there has been very little effort verifying these models beyond the system designs and locations on which they were based. Moreover, major PV modeling software products have not yet incorporated any of these models into their workflows. In response to this deficiency, we have integrated the methodology of the snow model developed in the paper by Marion et al. (2013) into the National Renewable Energy Laboratory's (NREL) System Advisor Model (SAM). In this work, we describe how the snow model is implemented in SAM and we discuss our demonstration of the model's effectiveness at reducing error in annual estimations for three PV arrays. Next, we use this new functionality in conjunction with a long term historical data set to estimate average snow losses across the United States for two typical PV system designs. The open availability of the snow loss estimation capability in SAM to the PV modeling community, coupled with our results of the nationwide study, will better equip the industry to accurately estimate PV energy production in areas affected by snowfall.

14 SOLAR ENERGY↗
DOE OSTI2015

Integration, Validation, and Application of a PV Snow Coverage Model in SAM

Due to the increasing deployment of PV systems in snowy climates, there is significant interest in a method capable of estimating PV losses resulting from snow coverage that has been verified for a wide variety of system designs and locations. A scattering of independent snow coverage models have been developed over the last 15 years; however, there has been very little effort spent on verifying these models beyond the system design and location on which they were based. Moreover, none of the major PV modeling software products have incorporated any of these models into their workflow. In response to this deficiency, we have integrated the methodology of the snow model developed in the paper by Marion et al. [1] into the National Renewable Energy Laboratory's (NREL) System Advisor Model (SAM). In this work we describe how the snow model is implemented in SAM and discuss our demonstration of the model's effectiveness at reducing error in annual estimations for two PV arrays. Following this, we use this new functionality in conjunction with a long term historical dataset to estimate average snow losses across the United States for a typical PV system design. The open availability of the snow loss estimation capability in SAM to the PV modeling community, coupled with our results of the nation-wide study, will better equip the industry to accurately estimate PV energy production in areas affected by snowfall.

14 SOLAR ENERGY↗
DOE OSTI2017

Thermochimica

Thermochimica is a software library that determines a unique combination of phases and their compositions at thermochemical equilibrium. Thermochimica can be used for stand-alone calculations or it can be directly coupled to other codes. This release of the software does not have a graphical user interface (GUI) and it can be executed from the command line or from an Application Programming Interface (API). Also, it is not intended for thermodynamic model development or for constructing phase diagrams. The main purpose of the software is to be directly coupled with a multi-physics code to provide material properties and boundary conditions for various physical phenomena. Significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. Various useful parameters can be provided as output from Thermochimica, such as: determination of which phases are stable at equilibrium, the mass of solution species and phases at equilibrium, mole fractions of solution phase constituents, thermochemical activities (which are related to partial pressures for gaseous species), chemical potentials of solution species and phases, and integral Gibbs energy (referenced relative to standard state). The overall goal is to provide an open source computational tool to enhance the predictive capability of multi-physics codes without significantly impeding computational performance.

Simunovic, Srdjan↗
DOE OSTI2014

Broadband Heating Rate Profile Project (BBHRP) - SGP 1bbhrpripbe1mcfarlane

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

1bbhrpripbe1mcfarlane↗
DOE OSTI2014

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe1mcfarlane

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Broadband Heating Rate Profile Project (BBHRP) - SGP ripbe370mcfarlane

The objective of the ARM Broadband Heating Rate Profile (BBHRP) Project is to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Required inputs to BBHRP include surface albedo and profiles of atmospheric state (temperature, humidity), gas concentrations, aerosol properties, and cloud properties. In the past year, the Radiatively Important Parameters Best Estimate (RIPBE) VAP was developed to combine all of the input properties needed for BBHRP into a single gridded input file. Additionally, an interface between the RIPBE input file and the RRTM was developed using the new ARM integrated software development environment (ISDE) and effort was put into developing quality control (qc) flags and provenance information on the BBHRP output files so that analysis of the output would be more straightforward. This new version of BBHRP, sgp1bbhrpripbeC1.c1, uses the RIPBE files as input to RRTM, and calculates broadband SW and LW fluxes and heating rates at 1-min resolution using the independent column approximation. The vertical resolution is 45 m in the lower and middle troposphere to match the input cloud properties, but is at coarser resolution in the upper atmosphere. Unlike previous versions, the vertical grid is the same for both clear-sky and cloudy-sky calculations.

54 ENVIRONMENTAL SCIENCES↗