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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

RECOVERY ACT - Methods for Decision under Technological Change Uncertainty and Risk Assessment for Integrated Assessment of Climate Change

This report presents the final outcomes and products of the project as performed both at the Massachusetts Institute of Technology and subsequently at Pennsylvania State University. The research project can be divided into three main components: methodology development for decision-making under uncertainty, improving the resolution of the electricity sector to improve integrated assessment, and application of these methods to integrated assessment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

RECOVERY ACT - Methods for Decision under Technological Change Uncertainty and Risk Assessment for Integrated Assessment of Climate Change

This report presents the final outcomes and products of the project as performed at the Massachusetts Institute of Technology. The research project consists of three main components: methodology development for decision-making under uncertainty, improving the resolution of the electricity sector to improve integrated assessment, and application of these methods to integrated assessment. Results in each area is described in the report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Looking under the hood: A comparison of techno-economic assumptions across national and global integrated assessment models

Integrated assessment models are extensively used in the analysis of climate change mitigation and are informing national decision makers as well as contribute to international assessments such as those of the Intergovernmental Panel on Climate Change. This paper conducts a comprehensive review of techno-economic assumptions in the electricity sector among sixteen different global and national integrated assessment models. Particular focus is given to six major economies in the world: Brazil, China, the EU, India, Japan and the US. The comparison reveals that techno-economic characteristics are quite different across integrated assessment models, both for the base year and future years. It is, however, important to recognize that techno-economic assessments from the literature exhibit an equally large range of parameters as the integrated assessment models reviewed. Beyond numerical differences, the representation of technologies also differs among models which needs to be taken into account when comparing numerical parameters. While desirable from a first principles perspective and often called for, it seems difficult to fully harmonize techno-economic parameters across a broader range of models due to structural differences in the representation of technology. Therefore, in the future making techno-economic parameters available together with of the technology representation as well as the exact definitions of the parameters should become the standard approach as it allows an open discussion of appropriate assumptions.

Krey, Volker↗
DOE OSTI2016

The National Risk Assessment Partnership’s integrated assessment model for carbon storage: A tool to support decision making amidst uncertainty

The US DOE-funded National Risk Assessment Partnership (NRAP) has developed an integrated assessment model (NRAP-IAM-CS) that can be used to simulate carbon dioxide (CO 2 ) injection, migration, and associated impacts at a geologic carbon storage site. The model, NRAP-IAM-CS, incorporates a system-modeling-based approach while taking into account the full subsurface system from the storage reservoir to groundwater aquifers and the atmosphere. The approach utilizes reduced order models (ROMs) that allow fast computations of entire system performance even for periods of hundreds to thousands of years. The ROMs are run in Monte Carlo mode allowing estimation of uncertainties of the entire system without requiring long computational times. The NRAP-IAM-CS incorporates ROMs that realistically represent several key processes and properties of storage reservoirs, wells, seals, and groundwater aquifers. Results from the NRAP-IAM-CS model are used to quantify risk profiles for selected parameter distributions of reservoir properties, seal properties, numbers of wells, well properties, thief zones, and groundwater aquifer properties. A series of examples is used to illustrate how the risk under different storage conditions evolves over time, both during injection, in the near-term post injection period, and over the long term. Finally, it is also shown how results from NRAP-IAM-CS can be used to investigate the importance of different parameters on risk of leakage and risk of groundwater contamination under different storage conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Model Evaluation and Hindcasting: An Experiment with an Integrated Assessment Model

Integrated assessment models have been extensively used for analyzing long term energy and greenhouse emissions trajectories and have influenced key policies on this subject. Though admittedly these models are focused on the long term trajectories, how well these models are able to capture historical dynamics is an open question. In a first experiment of its kind, we present a framework for evaluation of such integrated assessment models. We use Global Change Assessment Model for this zero order experiment, and focus on the building sector results for USA. We calibrate the model for 1990 and run it forward up to 2095 in five year time steps. This gives us results for 1995, 2000, 2005 and 2010 which we compare to observed historical data at both fuel level and service level. We focus on bringing out the key insights for the wider process of model evaluation through our experiment with GCAM. We begin with highlighting that creation of an evaluation dataset and identification of key evaluation metric is the foremost challenge in the evaluation process. Our analysis highlights that estimation of functional form of the relationship between energy service demand, which is an unobserved variable, and its drivers is a significant challenge in the absence of adequate historical data for both the dependent and driver variables. Historical data availability for key metrics is a serious limiting factor in the process of evaluation. Interestingly, service level data against which such models need to be evaluated are itself a result of models. Thus for energy services, the best we can do is compare our model results with other model results rather than observed and measured data. We show that long term models, by the nature of their construction, will most likely underestimate the rapid growth in some services observed in a short time span. Also, we learn that modeling saturated energy services like space heating is easier than modeling unsaturated services like space cooling and understanding that how far a service is from its saturation level is a key question which we probably don’t have an answer to. Finally and most importantly, even if long term models partially miss the short term dynamics, the long term insights provides by these models is fairly robust. We conclude by highlighting that our work is the first step in the much wider process of integrated assessment model evaluation and will hence have its own limitations. Future evaluation research work should build upon this zero order experiment for improving our modeling of human and coupled earth systems.

building energy↗
DOE OSTI2014

Integrated assessment of global water scarcity over the 21st century under multiple climate change mitigation policies

Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change and climate mitigation policies, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14 geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5 o x 0.5o resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W/m2 (equivalent to the SRES A1Fi emission scenario) and three climate policy scenarios with increasing mitigation stringency of 7.7, 5.5, and 4.2 W/m2 (equivalent to the SRES A2, B2, and B1 emission scenarios, respectively), we investigate the effects of emission mitigation policies on water scarcity. Two carbon tax regimes (a universal carbon tax (UCT) which includes land use change emissions, and a fossil fuel and industrial emissions carbon tax (FFICT) which excludes land use change emissions) are analyzed. The baseline scenario results in more than half of the world population living under extreme water scarcity by the end of the 21st century. Additionally, in years 2050 and 2095, 36% (28%) and 44% (39%) of the global population, respectively, is projected to live in grid cells (in basins) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). When comparing the climate policy scenarios to the baseline scenario while maintaining the same baseline socioeconomic assumptions, water scarcity declines under a UCT mitigation policy but increases with a FFICT mitigation scenario by the year 2095 particularly with more stringent climate mitigation targets. Under the FFICT scenario, water scarcity is projected to increase driven by higher water demands for bio-energy crops.

climate policy↗
DOE OSTI2018

Single-Shell Tank Structural Integrity Assessment Report

Integrity assessments are required to determine that the existing single-shell tanks (SST) located at the Hanford Site have structural integrity such that they will not collapse, rupture, or fail. This is a requirement of the Hanford Federal Facility Agreement and Consent Order Tri-Party Agreement (TPA)1 Change Request M-45-10-01 which established SST Integrity Project interim milestones and targets in January 2011. Interim Milestone M-045-91I established the requirement for this SST structural integrity assessment to be completed with an Independent Qualified Registered Professional Engineer (IQRPE) certification by September 30, 2018.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

An integrated assessment of location-dependent scaling for microalgae biofuel production facilities

Successful development of a large-scale microalgae-based biofuels industry requires comprehensive analysis and understanding of the feedstock supply chain—from facility siting and design through processing and upgrading of the feedstock to a fuel product. The evolution from pilot-scale production facilities to energy-scale operations presents many multi-disciplinary challenges, including a sustainable supply of water and nutrients, operational and infrastructure logistics, and economic competitiveness with petroleum-based fuels. These challenges are partially addressed by applying the Integrated Assessment Framework (IAF) – an integrated multi-scale modeling, analysis, and data management suite – to address key issues in developing and operating an open-pond microalgae production facility. This is done by analyzing how variability and uncertainty over space and through time affect feedstock production rates, and determining the site-specific “optimum” facility scale to minimize capital and operational expenses. This approach explicitly and systematically assesses the interdependence of biofuel production potential, associated resource requirements, and production system design trade-offs. To provide a baseline analysis, the IAF was applied in this paper to a set of sites in the southeastern U.S. with the potential to cumulatively produce 5 billion gallons per year. Finally, the results indicate costs can be reduced by scaling downstream processing capabilities to fit site-specific growing conditions, available and economically viable resources, and specific microalgal strains.

09 BIOMASS FUELS↗
DOE OSTI2018

A Methodology and Implementation of Automated Emissions Harmonization for Use in Integrated Assessment Models

Emissions harmonization refers to the process used to match greenhouse gas (GHG) and air pollutant results from Integrated Assessment Models (IAMs) against a common source of historical emissions. To date, harmonization has been performed separately by individual modeling teams. For the hand-over of emission data for the Shared Socio-economic Pathways (SSPs) to climate model groups, a new automated approach based on commonly agreed upon algorithms was developed. This work describes the novel methodology for determining such harmonization methods and an open-source Python software library implementing the methodology. Results are shown for two example scenarios (with and without climate policy cases) using the MESSAGE-GLOBIOM IAM that satisfactorily harmonize over 96% of the total emissions trajectories while having a negligible eect on key long-term climate indicators. This new capability enhances the comparability across dierent models, increases transparency and robustness of results, and allows other teams to easily participate in intercomparison exercises by using the same, openly available harmonization mechanism.

intergrated assessment, climate change, Harmonizat↗
DOE OSTI2022

FAST-1.1: Integral Assessment

An integral assessment has been performed to quantify the predictive capabilities of FAST, a thermal-mechanical nuclear fuel performance code designed to analyze fuel behavior from beginning of life to burnup levels allowed by the U.S. Nuclear Regulatory Commission (NRC). FAST code calculations are shown to compare satisfactorily to a preselected set of experimental data with both steady-state and anticipated operating occurrence (AOO) conditions and design basis accident (DBA) transient operating conditions. This document describes the assessment of FAST-1.1, the latest version of FAST, released April 2022. Abstract

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

FAST-1.2: Integral Assessment

An integral assessment has been performed to quantify the predictive capabilities of FAST, a thermal-mechanical nuclear fuel performance code designed to analyze fuel behavior from beginning of life to burnup levels allowed by the U.S. Nuclear Regulatory Commission (NRC). FAST code calculations are shown to compare satisfactorily to a preselected set of experimental data with both steady-state and anticipated operating occurrence (AOO) conditions and design basis accident (DBA) transient operating conditions. This document describes the assessment of FAST-1.2, the latest version of FAST, released March 2023.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

FAST-1.2.2: Integral Assessment

This integral assessment quantifies the predictive capabilities of Fuel Analysis under Steady-state and Transients (FAST), a thermal-mechanical nuclear fuel performance code designed to analyze fuel behavior from beginning of life to burnup levels allowed by the U.S. Nuclear Regulatory Commission. FAST code calculations are shown to compare satisfactorily to a pre-selected set of experimental data with both steady-state and anticipated operating occurrence conditions and design basis accident transient operating conditions. This document describes the assessment of FAST-1.2.2, the latest version of FAST, released April 2026.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Balancing global water availability and use at basin scale in an integrated assessment model

Water is essential for the world’s food supply, for energy production, including bioenergy and hydroelectric power, and for power system cooling. Water is already scarce in many regions of the world and could present a critical constraint as society attempts simultaneously to mitigate climate forcing and adapt to climate change, and to provide for a larger and more prosperous human population. Numerous studies have pointed to growing pressures on the world’s scarce fresh water resources from population and economic growth, and climate change. This study goes further. We use the Global Change Assessment Model to analyze interactions between population, economic growth, energy, land and water resources simultaneously in a dynamically evolving system where competing claims on water resources from all claimants—energy, land, and economy—are reconciled with water resource availability—from renewable water, non-renewable groundwater sources and desalinated water—across 14 geopolitical regions, 151 agriculture-ecological zones, and 235 major river basins. We find that previous estimates of global water withdrawal projections are overestimated. Model simulations show that it is more economical in some basins to alter agricultural and energy activities rather than utilize non-renewable groundwater or desalinated water. This study highlights the importance of accounting for water as a binding factor in agriculture, energy and land use decisions in IAMs and implications for global responses to water scarcity, particularly in the trade of agricultural commodities and land-use decisions.

basin↗
DOE OSTI2021

Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks

Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.

Bayesian network, Risk assessment, Monitoring, car↗