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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

A queueing model of pilot decision making in a multi-task flight management situation

Allocation of decision making responsibility between pilot and computer is considered and a flight management task, designed for the study of pilot-computer interaction, is discussed. A queueing theory model of pilot decision making in this multi-task, control and monitoring situation is presented. An experimental investigation of pilot decision making and the resulting model parameters are discussed.

Walden, R. S.↗
DOE OSTI2025

Automated Fire Detection for Industrial Settings with Pretrained Convolutional Networks

Early fire detection in industrial environments is critical to preventing equipment damage, personal injury, and operational disruptions. Traditional smoke detectors, while effective, often experience delays due to the time required for smoke to reach sensors, allowing fires to spread. Manual fire watch operations and human surveillance of camera feeds are resource-intensive and prone to human error. To address these challenges, this paper explores the application of convolutional neural networks for automated fire detection, specifically in industrial settings. By leveraging 11 different pre-trained machine vision models from TensorFlow and enhancing them with transfer learning on a custom-built industrial fire dataset, we optimized fire detection performance. Here, we analyzed each machine vision model architecture in terms of its depth, width, and input image resolution, considering both resource requirements and detection accuracy. We further explored the option of combining multiple models into an ensemble classifier to evaluate whether the performance improvements could justify the much greater computational complexity and other practical impacts. A cost-benefit analysis is presented to evaluate the trade-offs between performance and computational expense. Our findings identify that EfficientNetV2L, specifically tailored for industrial applications, provides the optimal balance between costs involved in training and using the model versus the overall fire detection performance. Additionally, we present a qualitative analysis of model performance using the technique of gradient-based class activation mapping to provide explainability by visualizing model decisions.

artificial intelligence↗
DOE OSTI2023

Estimating the electric vehicle charging demand of multi-unit dwelling residents in the United States

Abstract Early battery electric vehicle (EV) adopters can access home chargers for reliable charging. As the EV market grows, residents of multi-unit dwellings (MUDs) may face barriers in owning EVs and charging them without garage or parking availability. To investigate the mechanisms that can bridge existing disparities in home charging and station deployment, we characterized the travel behavior of MUD residents and estimated their EV residential charging demand. This study classifies the travel patterns of MUD residents by fusing trip diary data from the National Household Travel Survey and housing features from the American Housing Survey. A hierarchical agglomerative clustering method was used to cluster apartment complex residents’ travel profiles, considering attributes such as dwell time, daily vehicle miles traveled (VMT), income, and their residences’ US census division. We propose a charging decision model to determine the charging station placement demand in MUDs and the charging energy volume expected to be consumed, assuming that MUD drivers universally operate EVs in urban communities. Numerical experiments were conducted to gain insight into the charging demand of MUD residents in the US. We found that charging availability is indispensable for households that set out to meet 80% state of charge by the end of the day. When maintaining a 20% comfortable state of charge the entire day, the higher the VMT are, the greater the share of charging demand and the greater the energy use in MUD chargers. The upper-income group requires a greater share of MUD charging and greater daily kWh charged because of more VMT.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Robust Solution Approach for Bilevel Demand Response Game at Distribution Level

In this paper, a bilevel electricity pricing and demand response game between a distribution system operator (DSO) and load aggregators (LAs) is considered, and a robust decision model is proposed for the DSO to deal with the uncertainties from the wholesale market prices and demand consumptions of LAs. With the max-min objective at the upper level, the robust bilevel model is converted into a single level model by the Karush-Kuhn-Tucker (KKT) conditions and prime-dual transformation. Several groups of experiments have been conducted based on different preferences on uncertainty gaps and peak load reductions to show its effectiveness. After-the-fact scenario analysis has indicated that the robust solution is more beneficial in reducing the risk of inaccurate predictions as compared to the risk neutral strategy.

Chen, Yang↗
DOE OSTI2025

Balancing Trade-offs: Adaptive Differential Privacy in Interpretable Machine Learning Models

In the advancing field of machine learning, balancing accuracy, interpretability, and privacy represents a significant challenge. The problem is exacerbated by the widespread deployment of pre-trained models locally in diverse applications, which could lead to various amounts of privacy leakage. Conventional Differential Privacy strategies, in which uniform noises are applied to model gradients, guarantee data privacy at the expense of accuracy and interpretability. This paper introduces a Feature-Sensitive Adaptive Differential Privacy (FADP) framework with a unique noise-adding strategy. Noises are adaptively added based on feature importance clustering, where important features are considered for interpretability. By employing a unique masking technique, FADP selectively preserves crucial features with minimal noise interference, maintaining accuracy while enhancing interpretability. The FADP framework addresses the limitations of traditional DP methods by preserving critical channels and improving interpretability — a vital requirement in machine learning applications that demand transparency in model decisions. Through comprehensive testing, FADP is shown to balance the trade-offs among accuracy, privacy, and interpretability, marking a substantial advancement in the field of privacy-preserving machine learning.

Farhad Riya, Farhin [University of Tennessee, Knox↗
DOE OSTI2022

Partner with a Third-Party Delivery Service or Not? A Prediction-and-Decision Tool for Restaurants Facing Takeout Demand Surges During a Pandemic

Amidst the COVID-19 pandemic, restaurants become more reliant on no-contact pick-up or delivery ways for serving customers. As a result, they need to make tactical planning decisions such as whether to partner with online platforms, to form their own delivery team, or both. In this paper, we develop an integrated prediction-decision model to analyze the profit of combining the two approaches and to decide the needed number of drivers under stochastic demand. We first use the susceptible-infected-recovered (SIR) model to forecast future infected cases in a given region and then construct an autoregressive-moving-average (ARMA) regression model to predict food-ordering demand. Using predicted demand samples, we formulate a stochastic integer program to optimize food delivery plans. We conduct numerical studies using COVID-19 data and food-ordering demand data collected from local restaurants in Nuevo Leon, Mexico, from April to October 2020, to show results for helping restaurants build contingency plans under rapid market changes. Our method can be used under unexpected demand surges, various infection/vaccination status, and demand patterns. Here, our results show that a restaurant can benefit from partnering with third-party delivery platforms when (i) the subscription fee is low, (ii) customers can flexibly decide whether to order from platforms or from restaurants directly, (iii) customers require more efficient delivery, (iv) average delivery distance is long, or (v) demand variance is high.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Blueprint: Stakeholder-Specific Vulnerability Categorization Guidance

Vulnerability management is a process of discovering, analyzing, and handling new or reported security vulnerabilities in systems to prevent the systems from being exploited, to reduce risk, and to protect assets. For vulnerability analysis, handling, and response, the prioritization of organizational and analyst resources must precede. The Common Vulnerability Scoring System (CVSS) is a standard prioritization method that is used to rate the severity of security vulnerabilities in systems by assigning numerical severity scores, but it does not provide clear guidelines of how the numerical severity scores might inform decisions. The Stakeholder-Specific Vulnerability Categorization (SSVC) provides a method for prioritizing vulnerabilities based on the needs of the stakeholders involved in the vulnerability management process. Instead of the numerical scoring used in the CVSS, the SSVC focuses on contextual decision-making to determine how quickly and effectively an organization should respond to vulnerabilities. The main functionality of the SSVC accommodates the diversity of the stakeholders in the vulnerability management process, including finders, vendors, coordinators, deployers, and others. So, the SSVC should be designed to be used by any of these stakeholders, and it should be customizable to enable specific stakeholder decision models and risk appetites.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1972

Weather forecasts, users' economic expenses and decision strategies

Differing decision models and operational characteristics affecting the economic expenses (i.e., the costs of protection and losses suffered if no protective measures have been taken) associated with the use of predictive weather information have been examined.

Carter, G. M.↗
NASA NTRS1975

Community perspectives

General aviation is considered from the perspective of the local community's decision-making process in determining its needs for access to general aviation services. The decision-making model, preliminary decision, community characteristics, and planning processes are discussed.

Source record↗
NASA NTRS1976

Screening analysis and selection of emission reduction concepts for intermittent combustion aircraft engines

An analysis was conducted to screen, evaluate, and select three engine exhaust emission reduction concepts from a group of 14 candidate alternatives. A comprehensive literature search was conducted to survey the emission reduction technology state-of-the-art and establish contact with firms working on intermittent combustion engine development and pollution reduction problems. Concept development, advantages, disadvantages, and expected emission reduction responses are stated. A set of cost effectiveness criteria was developed, appraised for relative importance, and traded off against each concept so that its merit could be determined. A decision model was used to aid the evaluators in managing the criteria, making consistent judgements, calculating merit scores, and ranking the concepts. An Improved Fuel Injection System, Improved Cooling Combustion Chamber, and a Variable Timing Ignition System were recommended to NASA for approval and further concept development. An alternate concept, Air Injection, was also recommended.

Rezy, B. J.↗
NASA NTRS1976

Vibroacoustic test plan evaluation: Parameter variation study

Statistical decision models are shown to provide a viable method of evaluating the cost effectiveness of alternate vibroacoustic test plans and the associated test levels. The methodology developed provides a major step toward the development of a realistic tool to quantitatively tailor test programs to specific payloads. Testing is considered at the no test, component, subassembly, or system level of assembly. Component redundancy and partial loss of flight data are considered. Most and probabilistic costs are considered, and incipient failures resulting from ground tests are treated. Optimums defining both component and assembly test levels are indicated for the modified test plans considered. modeling simplifications must be considered in interpreting the results relative to a particular payload. New parameters introduced were a no test option, flight by flight failure probabilities, and a cost to design components for higher vibration requirements. Parameters varied were the shuttle payload bay internal acoustic environment, the STS launch cost, the component retest/repair cost, and the amount of redundancy in the housekeeping section of the payload reliability model.

Stahle, C. V.↗
NASA NTRS1977

Shuttle payload vibroacoustic test plan evaluation. Free flyer payload applications and sortie payload parametric variations

A preliminary assessment of vibroacoustic test plan optimization for free flyer STS payloads is presented and the effects on alternate test plans for Spacelab sortie payloads number of missions are also examined. The component vibration failure probability and the number of components in the housekeeping subassemblies are provided. Decision models are used to evaluate the cost effectiveness of seven alternate test plans using protoflight hardware.

Stahle, C. V.↗
NASA NTRS1978

Executive summary: Benefit-cost evaluation of an intra-regional air service in the Bay Area and a technology assessment of transportation system investments

The benefits and costs that would result from an intra-regional air service operation in the San Francisco Bay area were determined by utilizing an iterative statistical decision model to evaluate combinations of commuter airport sites and surface transportation facilities in conjunction with service by a given commuter aircraft type in light of area regional growth alternatives and peak and off-peak regional travel patterns. The model evaluates such transportation option with respect to criteria of airline profitability, public acceptance, and public and private non-user costs. In so doing, it incorporates information on modal split, peak and off-peak use of the air commuter fleet, terminal and airport costs, development costs and uses of land in proximity to the airport sites, regional population shifts, and induced zonal shifts in travel demand. The model is multimodal in its analytic capability, and performs exhaustive sensitivity analysis.

Haefner, L. E.↗
NASA NTRS1978

Parametric evaluation of the cost effectiveness of Shuttle payload vibroacoustic test plans

Consideration is given to alternate vibroacoustic test plans for sortie and free flyer Shuttle payloads. Statistical decision models for nine test plans provide a viable method of evaluating the cost effectiveness of alternate vibroacoustic test plans and the associated test levels. The methodology is a major step toward the development of a useful tool for the quantitative tailoring of vibroacoustic test programs to sortie and free flyer payloads. A broader application of the methodology is now possible by the use of the OCTAVE computer code.

Stahle, C. V.↗
NASA NTRS1986

Reduced modeling of flexible structures for decentralized control

Based upon the modified finite element-transfer matrix method, this paper presents a technique for reduced modeling of flexible structures for decentralized control. The modeling decisions are carried out at (finite-) element level, and are dictated by control objectives. A simply supported beam with two sets of actuators and sensors (linear force actuator and linear position and velocity sensors) is considered for illustration. In this case, it is conjectured that the decentrally controlled closed loop system is guaranteed to be at least marginally stable.

Yousuff, A.↗
NASA NTRS1989

Expert systems applied to spacecraft fire safety

Expert systems are problem-solving programs that combine a knowledge base and a reasoning mechanism to simulate a human expert. The development of an expert system to manage fire safety in spacecraft, in particular the NASA Space Station Freedom, is difficult but clearly advantageous in the long-term. Some needs in low-gravity flammability characteristics, ventilating-flow effects, fire detection, fire extinguishment, and decision models, all necessary to establish the knowledge base for an expert system, are discussed.

Smith, Richard L.↗
NASA NTRS1990

Evaluation of a proposed expert system development methodology: Two case studies

Two expert system development projects were studied to evaluate a proposed Expert Systems Development Methodology (ESDM). The ESDM was developed to provide guidance to managers and technical personnel and serve as a standard in the development of expert systems. It was agreed that the proposed ESDM must be evaluated before it could be adopted; therefore a study was planned for its evaluation. This detailed study is now underway. Before the study began, however, two ongoing projects were selected for a retrospective evaluation. They were the Ranging Equipment Diagnostic Expert System (REDEX) and the Backup Control Mode Analysis and Utility System (BCAUS). Both projects were approximately 1 year into development. Interviews of project personnel were conducted, and the resulting data was used to prepare the retrospective evaluation. Decision models of the two projects were constructed and used to evaluate the completeness and accuracy of key provisions of ESDM. A major conclusion reached from these case studies is that suitability and risk analysis should be required for all AI projects, large and small. Further, the objectives of each stage of development during a project should be selected to reduce the next largest area of risk or uncertainty on the project.

Gilstrap, Lewey↗