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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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Decision-Making for High Renewable Electricity Futures in the United States
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Multi-objective Decisions on Integrated Energy Systems Planning and Operation for Industrial Combined Heat and Power Supply
Unlike the power sector—which can transmit electricity over long distances via established grids—the industrial sector poses a unique challenge due to its geographically concentrated large-scale heat processes. Enhancing energy security in such industrial parks provides a dual benefit: reduced exposure to volatile fossil fuel prices and improved economic viability, largely driven by economies of scale in energy supply and distribution. This study presents a comprehensive technoeconomic analysis of a nuclear energy hub, employing a mechanism-focused approach to evaluate uncertainties in operational strategies and capacity optimization. Load profiles from three major energy intesive industries—chemical, refinery, and steelmaking—are examined, each presenting unique challenges and opportunities for nuclear energy integration. We adopt a multi-objective optimization framework, converting multiple objectives into a single objective function through the e-constraint method. The findings highlight clear trade-offs between system conditions and varying levels of energy independence. Overall, this analysis is granular enough to address industry-specific concerns yet sufficiently generalizable to provide actionable insights into the feasibility of nuclear-based clean heat solutions for the industrial sector.
Default effect versus active decision: Evidence from a field experiment in Los Alamos
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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.
Stereotactic Body Radiotherapy Versus Surgery for Medically Operable Stage I Non-Small-Cell Lung Cancer: A Markov Model-Based Decision Analysis
Purpose: To compare the quality-adjusted life expectancy and overall survival in patients with Stage I non-small-cell lung cancer (NSCLC) treated with either stereotactic body radiation therapy (SBRT) or surgery. Methods and Materials: We constructed a Markov model to describe health states after either SBRT or lobectomy for Stage I NSCLC for a 5-year time frame. We report various treatment strategy survival outcomes stratified by age, sex, and pack-year history of smoking, and compared these with an external outcome prediction tool (Adjuvant{exclamation_point} Online). Results: Overall survival, cancer-specific survival, and other causes of death as predicted by our model correlated closely with those predicted by the external prediction tool. Overall survival at 5 years as predicted by baseline analysis of our model is in favor of surgery, with a benefit ranging from 2.2% to 3.0% for all cohorts. Mean quality-adjusted life expectancy ranged from 3.28 to 3.78 years after surgery and from 3.35 to 3.87 years for SBRT. The utility threshold for preferring SBRT over surgery was 0.90. Outcomes were sensitive to quality of life, the proportion of local and regional recurrences treated with standard vs. palliative treatments, and the surgery- and SBRT-related mortalities. Conclusions: The role of SBRT in the medically operable patient is yet to be defined. Our model indicates that SBRT may offer comparable overall survival and quality-adjusted life expectancy as compared with surgical resection. Well-powered prospective studies comparing surgery vs. SBRT in early-stage lung cancer are warranted to further investigate the relative survival, quality of life, and cost characteristics of both treatment paradigms.
Predictors of Local Recurrence After Rituximab-Based Chemotherapy Alone in Stage III and IV Diffuse Large B-Cell Lymphoma: Guiding Decisions for Consolidative Radiation
Purpose: The role of consolidative radiation therapy (RT) for stage III and IV diffuse large B-cell lymphoma (DLBCL) in the era of rituximab is not well defined. There is evidence that some patients with bulky disease may benefit, but patient selection criteria are not well established. We sought to identify a subset of patients who experienced a high local failure rate after receiving rituximab-based chemotherapy alone and hence may benefit from the addition of consolidative RT. Methods and Materials: Two hundred eleven patients with stage III and IV DLBCL treated between August 1999 and January 2012 were reviewed. Of these, 89 had a complete response to systemic therapy including rituximab and received no initial RT. Kaplan-Meier analysis and Cox proportional hazards regression were performed, with local recurrence (LR) as the primary outcome. Results: The median follow-up time was 43.9 months. Fifty percent of patients experienced LR at 5 years. In multivariate analysis, tumor ≥5 cm and stage III disease were associated with increased risk of LR. The 5-year LR-free survival was 47.4% for patients with ≥5-cm lesions versus 74.7% for patients with <5-cm lesions (P=.01). In patients with <5-cm tumors, the maximum standardized uptake value (SUVmax) was ≥15 in all patients with LR. The 5-year LR-free survival was 100% in SUV<15 versus 68.8% in SUV≥15 (P=.10). Conclusions: Advanced-stage DLBCL patients with stage III disease or with disease ≥5 cm appear to be at an increased risk for LR. Patients with <5-cm disease and SUVmax ≥15 may be at higher risk for LR. These patients may benefit from consolidative RT after chemoimmunotherapy.
The Role of Circulating Tumor Cells in Breast Cancer and Implications for Radiation Treatment Decisions
Tumor biomarkers are used routinely in oncology to assign risk categorization, screen and assist in diagnosis of malignancy, allow for prognostication and prediction of outcomes and treatment response, and allow for monitoring of patients after treatment completion. Although tissue-based biomarkers have a long history of use, the emergence of liquid-based biomarkers, including circulating tumor cells (CTCs), may soon revolutionize the management of patients with cancer. Here, we review the discovery of CTCs and their role as prognostic and predictive biomarkers, with an emphasis on breast cancer. We discuss the platforms for CTC enumeration and focus on studies using the only US Food and Drug Administration–approved platform for CTC enumeration (CellSearch). In addition, we examine the role of CTCs in women with metastatic, inflammatory, and nonmetastatic breast cancer, as well as the clinical evidence for their use as a surrogate for radiation treatment response as well as surveillance after treatment. Finally, we conclude by investigating ongoing clinical studies assessing CTCs as radiation response predictors and discuss unanswered questions.
Dosimetric Planning Tradeoffs to Reduce Heart Dose Using Machine Learning-Guided Decision Support Software in Patients with Lung Cancer
Cardiac toxicity is a well-recognized risk after radiation therapy (RT) in patients with non-small cell lung cancer (NSCLC). However, the extent to which treatment planning optimization can reduce mean heart dose (MHD) without untoward increases in lung dose is unknown.
China's vehicle electrification impacts on sales, fuel use, and battery material demand through 2050: Optimizing consumer and industry decisions
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Decision support environment for medical product safety surveillance
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Decision-making under surprise and uncertainty: Arsenic contamination of water supplies
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Collaborative and trustworthy fault diagnosis for mechanical systems based on probabilistic neural network with decision-level information fusion
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A multicriteria decision analysis framework to measure equitable healthcare access during COVID-19
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Onsite strength determination for early-opening decision making of high early strength concrete pavement
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