Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “decision analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Spacelab experiment computer study. Volume 1: Executive summary (presentation)

A quantitative cost for various Spacelab flight hardware configurations is provided along with varied software development options. A cost analysis of Spacelab computer hardware and software is presented. The cost study is discussed based on utilization of a central experiment computer with optional auxillary equipment. Groundrules and assumptions used in deriving the costing methods for all options in the Spacelab experiment study are presented. The groundrules and assumptions, are analysed and the options along with their cost considerations, are discussed. It is concluded that Spacelab program cost for software development and maintenance is independent of experimental hardware and software options, that distributed standard computer concept simplifies software integration without a significant increase in cost, and that decisions on flight computer hardware configurations should not be made until payload selection for a given mission and a detailed analysis of the mission requirements are completed.

Lewis, J. L.↗
NASA NTRS2007

Crew Exploration Vehicle Ascent Abort Overview

One of the primary design drivers for NASA's Crew Exploration Vehicle (CEV) is to ensure crew safety. Aborts during the critical ascent flight phase require the design and operation of CEV systems to escape from the Crew Launch Vehicle and return the crew safely to the Earth. To accomplish this requirement of continuous abort coverage, CEV ascent abort modes are being designed and analyzed to accommodate the velocity, altitude, atmospheric, and vehicle configuration changes that occur during ascent. The analysis involves an evaluation of the feasibility and survivability of each abort mode and an assessment of the abort mode coverage. These studies and design trades are being conducted so that more informed decisions can be made regarding the vehicle abort requirements, design, and operation. This paper presents an overview of the CEV, driving requirements for abort scenarios, and an overview of current ascent abort modes. Example analysis results are then discussed. Finally, future areas for abort analysis are addressed.

Davidson, John B., Jr.↗
DOE OSTI2016

One System Overview - 16579

The U.S. Department of Energy (DOE), Office of River Protection (ORP) is responsible for managing and completing the River Protection Project mission, which is to 'safeguard the nuclear waste stored in Hanford's 177 underground tanks, and to manage the waste safely and responsibly until it can be treated in the Waste Treatment and Immobilization Plant for final disposition'. The Office of River Protection's work scope is currently performed through two primary contracts: - The Tank Operations Contract, held by Washington River Protection Solutions LLC, (WRPS) includes the construction, operation, and maintenance activities necessary to safely store, retrieve, and transfer tank wastes; provide supplemental tank waste treatment; provide storage and/or disposal of primary and secondary waste streams; design, construction and commissioning of the Low-Activity Waste Pretreatment System; and support ORP to integrate Hanford Tank Waste Treatment and Immobilization Plant (WTP) completion and startup with Tank Farms operations. - The WTP Contract, held by Bechtel National, Inc. (BNI), includes the design, construction, and commissioning of a Pretreatment Facility, two vitrification facilities (one for high-level waste and one for low-activity waste), a dedicated analytical laboratory, and supporting facilities to treat radioactive tank wastes by immobilizing them into a stable glass waste form. One System was established as a means to improve the integration between the tank farms and the WTP project to support its safe and successful startup. One System's scope and purpose focus on mission integration consistent with DOE's plans to treat tank waste in phases, starting with direct feed of the low-activity waste stream to the WTP's Low-Activity Waste (LAW) Vitrification Facility (referred to as DFLAW). The One System organization now has four major focus areas: - Flowsheet Integration? Integrated River Protection Project (RPP) flowsheet development and management; developing a gaps, risks, and opportunities management plan and technical roadmap; and waste feed qualification. - Mission Analysis and Planning? Strategic planning, system planning, and modeling integration. - WTP Startup, Commissioning, and Operations Integration? Interface Control Document (ICD) management, coordinating facilities startup-to-commissioning-to-operations, contract directives and standards identification, and DFLAW program integration. - Project Integration and Controls? Integrated schedule, metrics/dashboards monitoring, and One System risk register. ORP established the DFLAW Program Office in February 2015 as one of its key performance goals. ORP staff, along with contractor managers, have identified roles and responsibilities for the each of the four major focus areas. One System has established an Executive Council and Governance Board to drive program progress and make decisions on DFLAW. This approach allows appropriate government and contractor senior management involvement in the DFLAW Program. Monthly critical path analysis on the integrated DFLAW schedule is being performed. Interface control documents specific to DFLAW have been developed, and system planning and modeling tools are being used to help define the DFLAW flowsheet. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

R&D Roadmap for Enhanced Resilient Plant Systems, Metrics, Scenarios, Risk Analysis, and Modeling and Simulation

The nuclear industry and the U.S. Department of Energy are jointly developing accident tolerant fuel (ATF) which has the potential to greatly improve the safety and economic performance of the current fleet of NPPs. The combination of ATF with the optimal use of FLEX equipment (deployed as an industry response to the Fukushima Daiichi Nuclear Power Plant (NPP) accident in 2012), enhancements on plant components and systems, incorporation of augmented cooling systems or new passive cooling systems, and improvements in fuel cycle efficiency, have the potential to render the NPPs more efficient and resilient to events (both internally and externally initiated) that have the potential to challenge the integrity of the fuel or plant containment. In this report, combinations of these plant improvements are called Enhanced Resilient Plant Systems. In order to accelerate the development and deployment of the components that comprise Enhanced Resilient Plant Systems, a well-integrated toolkit that is fuel/clad-, fuel cycle-, systems-, and scenario-centric is required to provide a ready platform for the analysis of the advanced ATF fuel and cladding materials that are being developed, as well as plant systems modifications to achieve enhanced resiliency. Since the deployment of these enhancements will comprise a risk/benefit tradeoff of their impacts on plant safety and economics, the envisioned toolkit will need to be capable to characterizing the multidimensional aspects associated with these evaluations and provide decision-makers with information that can optimize the technological, economic, and safety benefits that are to be obtained. The Risk-Informed Systems Analysis (RISA) Pathway of the DOE Light Water Reactor Sustainability (LWRS) Program initiated several research tasks to develop analytical capabilities to support the industry in the transition to the ATF and Enhanced Resilient Plant Systems. The general idea behind the initiative is the development of an integrated evaluation approach which combines the plant probabilistic risk assessment (PRA) models with Multi-Physics Best Estimate Plus Uncertainty (MP-BEPU) analyses in a seamless fashion. The integrated evaluation framework aims at enabling plant system configuration variations to be studied with speed and precision, including detailed risk and benefit assessments of introducing ATF and Enhanced Resilient Plant Systems into current LWR plants to achieve both safety and operational performance enhancements. The focus of this report is to present an integrated research and development (R&D) roadmap to identify and perform high value evaluations of proposed ATF and Enhanced Resilient Plant Systems concepts to identify both the technical (e.g. benefits to risk, safety, and operational margins) and the economic (i.e. business and cost) elements associated with industry adoption of the technology. The integrated evaluation approach will be developed to support the development, testing, qualification, licensing, and deployment of ATF and Enhanced Resilient Plant Systems technology that is capable of achieving substantial safety and economic improvements as well as timely widespread adoption by the US nuclear industry.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1974

An analysis of wildfire prevention

A model of the production of wildfire ignitions and damages is developed and used to determine wildland activity-regulation decisions, which minimize total expected cost-plus-loss due to wildfires. In this context, the implications of various policy decisions are considered. The resulting decision rules take a form that makes it possible for existing wildfire management agencies to readily adopt them upon collection of the required data.

Heineke, J. M.↗
NASA NTRS2002

Glass-Cockpit Pilot Subjective Ratings of Predictive Information, Collocation, and Mission Status Graphics: An Analysis and Summary of the Future Focus of Flight Deck Research Survey

NASA Langley Research Center has been researching ways to improve flight crew decision aiding for systems management. Our current investigation is how to display a wide variety of aircraft parameters in ways that will improve the flight crew's situation awareness. To accomplish this, new means are being explored that will monitor the overall health of a flight and report the current status of the aircraft and forecast impending problems to the pilots. The initial step in this research was to conduct a survey addressing how current glass-cockpit commercial pilots would value a prediction of the status of critical aircraft systems. We also addressed how this new type of data ought to be conveyed and utilized. Therefore, two other items associated with predictive information were also included in the survey. The first addressed the need for system status, alerts and procedures, and system controls to be more logically grouped together, or collocated, on the flight deck. The second idea called for the survey respondents opinions on the functionality of mission status graphics; a display methodology that groups a variety of parameters onto a single display that can instantaneously convey a complete overview of both an aircraft's system and mission health.

Bartolone, Anthony↗
DOE OSTI2013

Evolution of US DOE Performance Assessments Over 20 Years - 13597

Performance assessments (PAs) have been used for many years for the analysis of post-closure hazards associated with a radioactive waste disposal facility and to provide a reasonable expectation of the ability of the site and facility design to meet objectives for the protection of members of the public and the environment. The use of PA to support decision-making for LLW disposal facilities has been mandated in United States Department of Energy (US DOE) directives governing radioactive waste management since 1988 (currently DOE Order 435.1, Radioactive Waste Management). Prior to that time, PAs were also used in a less formal role. Over the past 20+ years, the US DOE approach to conduct, review and apply PAs has evolved into an efficient, rigorous and mature process that includes specific requirements for continuous improvement and independent reviews. The PA process has evolved through refinement of a graded and iterative approach designed to help focus efforts on those aspects of the problem expected to have the greatest influence on the decision being made. Many of the evolutionary changes to the PA process are linked to the refinement of the PA maintenance concept that has proven to be an important element of US DOE PA requirements in the context of supporting decision-making for safe disposal of LLW. The PA maintenance concept is central to the evolution of the graded and iterative philosophy and has helped to drive the evolution of PAs from a deterministic compliance calculation into a systematic approach that helps to focus on critical aspects of the disposal system in a manner designed to provide a more informed basis for decision-making throughout the life of a disposal facility (e.g., monitoring, research and testing, waste acceptance criteria, design improvements, data collection, model refinements). A significant evolution in PA modeling has been associated with improved use of uncertainty and sensitivity analysis techniques to support efficient implementation of the graded and iterative approach. Rather than attempt to exactly predict the migration of radionuclides in a disposal unit, the best PAs have evolved into tools that provide a range of results to guide decision-makers in planning the most efficient, cost effective, and safe disposal of radionuclides. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2022

RF Environment Data Analysis for UAS Operations

As the usage of radio frequency spectrum and uncrewed aircraft systems continue to grow, the radio frequency environment and its implications to flight safety should be understood. This is important to ensure control and command links as well as data collection links maintain strong communications during flight. NASA System-Wide Safety (SWS) is currently developing standards of flight safety but lacks methods for establishing confidence in the availability of radio frequency space to make a go/no-go decision for drone flights. This study examines information about the radio modules used by SWS and how they interact with the RF environment though analysis of historical spectrum data. This review studies the potential effectiveness of observing the power spread and occupancy methods as they apply to the flight system radios. It has been determined that viewing the frequency and time when the environment is greater than a threshold which indicates potential interference levels may give insight into the patterns of spectrum usage.

Radio Frequency↗
DOE OSTI2014

Development of a Risk-Based Comparison Methodology of Carbon Capture Technologies

Given the varying degrees of maturity among existing carbon capture (CC) technology alternatives, an understanding of the inherent technical and financial risk and uncertainty associated with these competing technologies is requisite to the success of carbon capture as a viable solution to the greenhouse gas emission challenge. The availability of tools and capabilities to conduct rigorous, risk–based technology comparisons is thus highly desirable for directing valuable resources toward the technology option(s) with a high return on investment, superior carbon capture performance, and minimum risk. To address this research need, we introduce a novel risk-based technology comparison method supported by an integrated multi-domain risk model set to estimate risks related to technological maturity, technical performance, and profitability. Through a comparison between solid sorbent and liquid solvent systems, we illustrate the feasibility of estimating risk and quantifying uncertainty in a single domain (modular analytical capability) as well as across multiple risk dimensions (coupled analytical capability) for comparison. This method brings technological maturity and performance to bear on profitability projections, and carries risk and uncertainty modeling across domains via inter-model sharing of parameters, distributions, and input/output. The integration of the models facilitates multidimensional technology comparisons within a common probabilistic risk analysis framework. This approach and model set can equip potential technology adopters with the necessary computational capabilities to make risk-informed decisions about CC technology investment. The method and modeling effort can also be extended to other industries where robust tools and analytical capabilities are currently lacking for evaluating nascent technologies.

carbon capture↗
DOE OSTI2015

Preliminary Analysis of an Oscillating Surge Wave Energy Converter with Controlled Geometry: Preprint

The aim of this paper is to present a novel wave energy converter device concept that is being developed at the National Renewable Energy Laboratory. The proposed concept combines an oscillating surge wave energy converter with active control surfaces. These active control surfaces allow for the device geometry to be altered, which leads to changes in the hydrodynamic properties. The device geometry will be controlled on a sea state time scale and combined with wave-to-wave power-take-off control to maximize power capture, increase capacity factor, and reduce design loads. The paper begins with a traditional linear frequency domain analysis of the device performance. Performance sensitivity to foil pitch angle, the number of activated foils, and foil cross section geometry is presented to illustrate the current design decisions; however, it is understood from previous studies that modeling of current oscillating wave energy converter designs requires the consideration of nonlinear hydrodynamics and viscous drag forces. In response, a nonlinear model is presented that highlights the shortcomings of the linear frequency domain analysis and increases the precision in predicted performance.

17 WIND ENERGY↗
DOE OSTI2025

Physics-based hybrid machine learning for critical heat flux prediction with uncertainty quantification

Critical heat flux (CHF) is a key quantity in nuclear system modeling due to its impact on heat transfer, safety margins, and reactor performance. This study develops and validates an uncertainty-aware hybrid modeling approach that combines machine learning with physics-based models to predict CHF in cases of dryout. The Biasi and Bowring empirical correlations were paired with three ML uncertainty quantification (UQ) techniques: deep neural network (DNN) ensembles, Bayesian neural networks (BNNs), and deep Gaussian processes (DGPs). A pure ML model without a base model was evaluated for comparison. Model performance was assessed under plentiful (7,350 points) and limited (9 points) training data scenarios using parity, uncertainty distributions, and calibration curves. Results show that the Biasi hybrid DNN ensemble achieved the best overall performance, with a mean absolute relative error of 1.846%, and well-calibrated uncertainty estimates. The BNN-based hybrids showed slightly higher error (2.14%) but superior uncertainty calibration. DGP models underperformed, with over 6% error and poor uncertainty calibration. All hybrid models outperformed pure machine learning configurations, demonstrating resistance against data scarcity. These findings indicate that hybrid modeling significantly improves predictive accuracy, interpretability, and resilience to data scarcity. The integration of uncertainty awareness provides actionable confidence in CHF predictions, which is vital for safety-critical decisions in nuclear applications. This hybrid approach offers a viable pathway for deploying ML models in reactor analysis tools while preserving domain knowledge and physical consistency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

On choosing the resolution of normative models

Long time horizon normative models are frequently used for policy analysis, strategic planning, and system analysis. Choosing the granularity of the temporal or spatial resolution of such models is an important modeling decision, often having a first order impact on model results. This type of decision is frequently made by modeler judgment, specifically when the predictive power of alternative choices cannot be tested. In this paper, we show how the implicit tradeoffs modelers make in these formulation decisions, in particular in the tradeoff between the accuracy of representation enabled by the available data and model parsimony, may be addressed with established information theoretic ideas. The paper provides guidance for modelers making these tradeoffs or, in certain cases, enables explicit tests for assessing appropriate levels of resolution. Here, we focus on optimization based normative models in the discussion, and draw our examples from the energy and climate domain.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Breaking Down the Computational Barriers to Real-Time Urban Flood Forecasting

Flooding impacts are on the rise globally, and concentrated in urban areas. Currently, there are no operational systems to forecast flooding at spatial resolutions that can facilitate emergency preparedness and response actions mitigating flood impacts. We present a framework for real-time flood modeling and uncertainty quantification that combines the physics of fluid motion with advances in probabilistic methods. The framework overcomes the prohibitive computational demands of high-fidelity modeling in real-time by using a probabilistic learning method relying on surrogate models that are trained prior to a flood event. This shifts the overwhelming burden of computation to the trivial problem of data storage, and enables forecasting of both flood hazard and its uncertainty at scales that are vital for time-critical decision-making before and during extreme events. The framework has the potential to improve flood prediction and analysis and can be extended to other hazard assessments requiring intense high-fidelity computations in real-time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗
DOE OSTI2026

Developing a Process for Collaboration-Based Siting of a Federal Consolidated Interim Storage Facility in the United States: Learning from Communities Living with Legacy Waste

In June of 2023, the U.S. Department of Energy (DOE), Office of Nuclear Energy (NE) announced the selection of its Collaboration-Based Siting (CBS) Consortia, a group of 12 awardees, including the Consortium for Risk Evaluation with Stakeholder Participation (CRESP) (led by Vanderbilt University) to assist DOE-NE with the development of its process for siting a federal consolidated interim storage facility (FCISF) for spent nuclear fuel (SNF) storage. At this time, DOE NE is not soliciting interested host communities, rather the CBS Consortia are tasked with in-depth engagement, mutual learning, and capacity building to provide DOE NE with feedback on the CBS process. CRESP’s objective is to engage communities in two regions (the Pacific Northwest and the Southeast) with sites currently storing defense- and research-related SNF to foster learning concerning the best and worst practices in community participation in risk-informed decision making. This includes learning from existing structures for public input in radioactive waste management decision making [e.g. citizen advisory boards (CABs)] and other local parties about how to build and sustain trust among the parties. CRESP has been working to engage stakeholders and Tribes surrounding two DOE sites historically differing in receptiveness to engaging with DOE and trusting in DOE to accomplish its missions. CRESP’s approach to date has consisted of (1) engaging voluntarily members and former members of the DOE Office of Environmental Management’s CABs to develop a mutual understanding of their perspectives, values, and experiences related to risk and participatory decision making; (2) engaging members of those communities that would likely be part of any radioactive waste management discussions and who may provide valuable feedback for the development of the CBS process; and in the longer term, (3) engaging communities to foster knowledge sharing on understanding and definitions of risk and how risk is factored into community decision making. Our emphasis is to identify opportunities for improving risk communication frameworks, strategies, and decision making. The selection of a future FCISF site is likely to result in the creation of a structure similar to a CAB composed of members of the local community. We anticipate that these insights can help DOE NE learn from existing participatory risk communication structures in place at sites storing defenseor research-related SNF to understand best practices for fostering enduring and participatory relationships with future CABs. Within this paper, we (1) describe CRESP’s overall approach to assisting DOE NE with maturing the CBS process; (2) present a summary of preliminary phase 1 project results, including the development of a body of knowledge (describing available resources to support community engagement, risk communica tion, and participatory decision making) and community ecosystem information (leveraging demographic, social, economic, and environmental attribute mapping and advanced sentiment analysis of social media data); and (3) based on these results, provide observations for future research opportunities to support the development of CBS processes for radioactive waste management facilities, generally.

collaboration-based siting↗
DOE OSTI2021

Exploring PV Circularity by Modeling Socio-Technical Dynamics of Modules’ End-of-Life Management

The circular economy (CE) tackles environmental and resource scarcity issues by maximizing value retention in the economy. The concept implies design strategies such as reducing the use of materials or improving products’ durability and end-of-life (EOL) strategies, for example, reusing products and components and recycling materials. With an estimated 80 million tons of global cumulative EOL photovoltaic (PV) modules, applying CE principles to the PV industry could alleviate resource scarcity issues while also providing economic benefits. However, transitioning to a CE may imply changes in organizations and consumer behaviors. In this context, assessment of CE strategies may require accounting for behavioral change, a requirement that methods from complex system science such as agent-based modeling meet. Thus, this paper uses an agent-based modeling (ABM) approach to study circularity in the photovoltaics supply chain. Four types of agents are represented in the ABM: PV owners, installers, recyclers, and manufacturers. Moreover, five possible EOL options – including three CE strategies – are modeled. Departing from traditional techno-economic analysis, the model includes techno-economic factors as well as social factors to model EOL management decisions. Results show that each dollar decrease in the recycling fees improves the recycling rate by roughly 1.1%. However, excluding social factors underestimates the effect that lower recycling prices have on material circularity.

agent-based modeling↗