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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Mean-Variance Problems for Finite Horizon Semi-Markov Decision Processes

This paper deals with a mean-variance problem for finite horizon semi-Markov decision processes. The state and action spaces are Borel spaces, while the reward function may be unbounded. The goal is to seek an optimal policy with minimal finite horizon reward variance over the set of policies with a given mean. Using the theory of N-step contraction, we give a characterization of policies with a given mean and convert the second order moment of the finite horizon reward to a mean of an infinite horizon reward/cost generated by a discrete-time Markov decision processes (MDP) with a two dimension state space and a new one-step reward/cost under suitable conditions. We then establish the optimality equation and the existence of mean-variance optimal policies by employing the existing results of discrete-time MDPs. We also provide a value iteration and a policy improvement algorithms for computing the value function and mean-variance optimal policies, respectively. In addition, a linear program and the dual program are developed for solving the mean-variance problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Hyperplane decision trees as piecewise linear surrogate models for chemical process design

Recent trends in chemical engineering research point towards an increasing reliance on data-driven modeling approaches. Neural networks, for instance, have proven to be accurate when data is plentiful and high-dimensional, but in many cases, they require computationally-intensive training procedures. Here, in this work, we describe hyperplane decision trees (HT) as a highly expressive and low-compute machine learning model architecture. These models are locally linear and have linear decision boundaries, resulting in a piecewise linear model of the data. This property allows them to be converted into mixed-integer linear constraints which can be globally optimized. Our open-source PyTorch implementation of this method is a fast, flexible, and accessible way to build accurate piecewise linear models of data.

Decision trees↗
DOE OSTI2023

A decision support tool for e-waste recycling operations using the hen-and-chicks bio-inspired optimization metaheuristic

E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses face challenges to optimize their operational configuration to achieve better economic and environmental performance. To help e-waste recyclers mitigate this problem, we have developed a modular decision support tool called the Comprehensive Manufacturing Assessment Tool (CMAT) that can simulate both e-waste recycling operations and economics. This tool can give valuable insights regarding the profitability of the entire operation and different e-waste types. In addition, a new bio-inspired metaheuristic optimization algorithm, hen-and-chicks optimization (HACO), was developed to assign manpower to different workstations to maximize operational efficiencies. According to the results of our case study, laptops, desktops, and computer peripherals are the three electronic waste products that produce the most profit. Our examination of the sensitivity of material prices shows that the price of steel has the most significant influence on total profit, because it is the most widely used material in the majority of electronic devices. We have released the decision support tool as open-source software under a general public license. It could be customized for other recycling industries beyond e-waste to achieve business sustainability by making their operations more efficient.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Multi-criteria group decision-making based sustainability measurement of wastewater treatment processes

There are various processes which can be used for wastewater treatment (WT), and the selection of the most sustainable one among different processes is a hard task. This study aims at helping the decision-makers (DM) to address this by developing an intuitionistic fuzzy set (IFS) theory based group multi-attribute decision analysis (MADA) method. Ten criteria in environment, economy, society-politic, and technology dimensions were employed to achieve sustainability measurement (SM) of WT processes. The multi-criteria sustainability assessment method developed in this study allow different experts to attend the SM, and enable the participants to employ the natural language/words to depict their intuitionistic opinions. Accordingly, the proposed method can achieve group SM under uncertainties. An illustrative case including four processes for wastewater treatment, namely Anaerobic-Anoxic-Oxic (AAO) process, Triple Oxidation Ditch (TOD) process, Anaerobic single-ditch oxidation (ASD) process, and Sequencing batch reactor activated sludge process (SBR), has been studied, and the results reveal that this method can determine sustainability sequence of different WT processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ecological connectivity and in-kind mitigation in a regulatory decision framework: A case study with an amphibian habitat specialist

Ecological connectivity is critical to the survival and long-term viability of populations but is often overlooked in regulatory frameworks. We integrated landscape-level processes into a mitigation strategy for impacts to aquatic resources on the U.S. Department of Energy (DOE) Oak Ridge Reservation (ORR) in eastern Tennessee. Wetlands on the ORR, which contain significant breeding populations of the imperiled four-toed salamander (Hemidactylium scutatum) and tubercled rein orchid (Platanthera flava var. herbiola), will be impacted by construction of an environmental waste disposal facility under the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA). Here, we used a modified Kepner-Tregoe decision analysis to select general mitigation options that balanced regulatory requirements and interest group perspectives. We emphasized habitat connectivity through models that prioritized an area's importance to natural area connectivity (centrality) and maintenance of population structure for an affected habitat specialist (four-toed salamanders). We also emphasized in-kind mitigation through the preservation and enhancement of ecologically similar resources and the translocation and establishment of a new subpopulation of four-toed salamanders elsewhere on the ORR. We ultimately released over 500 juvenile salamanders that originated from the impacted site into the chosen mitigation wetlands. By doing so under the constraints of a time-sensitive CERCLA remediation effort and exceeding its substantive requirements, this work underscores feasibility. Ecological connectivity and the conservation of species that are not afforded explicit regulatory processes can be effectively and efficiently integrated into environmental decision-making and land use planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

An overview of emerging technologies in contemporary decision support system development

The rapid development of Web technology has opened a new approach to Decision Support System (DSS) development. For instance, Social Media is one of the Web 2.0 digital platforms that allow the creation and exchanges of user-generate content through an interactive interface, high user control and mass participation. The concept and characteristics of Web 2.0 such as remote, platform-independent, context-rich and easy to use, which is fulfill the concept and purpose of DSS. This paper outlines some of the elementary concepts of Web 2.0 and social media technology which can be potentially integrated within DSS to enhance the decision-making process. Our initial investigation indicates that there is limited study attempt to embed Web 2.0 into DSS. Thus, this paper highlights the importance of Web 2.0 technology in order to foster the betterment of DSS development and its usability.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient’s health condition using data from a wearable device considers in this article.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Design and implementation of wireless dose logger network for radiological emergency decision support system

A decision support system (DSS) is implemented in Radiological Safety Division, Indira Gandhi Centre for Atomic Research for providing guidance for emergency decision making in case of an inadvertent nuclear accident. Real time gamma dose rate measurement around the stack is used for estimating the radioactive release rate (source term) by using inverse calculation. Wireless gamma dose logging network is designed, implemented, and installed around the Madras Atomic Power Station reactor stack to continuously acquire the environmental gamma dose rate and the details are presented in the paper. The network uses XBee–Pro wireless modules and PSoC controller for wireless interfacing, and the data are logged at the base station. A LabView based program is developed to receive the data, display it on the Google Map, plot the data over the time scale, and register the data in a file to share with DSS software. The DSS at the base station evaluates the real time source term to assess radiation impact.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Navigating Uncertainty: Challenges in Visualizing Ensemble Data and Surrogate Models for Decision Systems

Uncertainty visualization plays a critical role in transforming ensemble simulation data into actionable insights by effectively communicating various dimensions of uncertainty within a system. The emergence of artificial intelligence-driven surrogate models trained on multirun ensemble data offers a transformative opportunity to replace computationally intensive simulations with fast estimates, enabling users to explore data spaces with unprecedented depth and interactivity. However, integrating ensemble data and surrogate models into decision-making workflows and tools introduces novel challenges for uncertainty visualization. These include reconciling and clearly communicating the unique uncertainties associated with ensembles and their surrogate model estimates, and leveraging these approximations to inform actionable decisions. This work explores these challenges in the context of high-dimensional data visualization, bridging discrete datasets with their continuous representations and addressing the complexities of systems that support iterative navigation between input and output spaces. We evaluate the role of uncertainty visualization in fostering intuitive, actionable interactions and identify critical hurdles in advancing this frontier of computational simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Decision-Dependent Uncertainty-Aware Distribution System Planning Under Wildfire Risk

The interaction between power systems and wildfires can be dangerous and costly. Distribution grids can be liable for the outbreak of wildfires during extreme weather. In wildfire-prone areas, investment planning should consider the impact of operational actions on wildfire-related uncertainties affecting line failure likelihood. Here, in this case, endogenous-based uncertainty modeling should comprise the backbone of the investment planning model viz-a-viz the inability of standard exogenous-based uncertainty modeling. Therefore, we propose a decision-dependent uncertainty (DDU) aware methodology to optimize investment portfolios for distribution systems, considering that high power-flow levels in high-threat areas can ignite wildfires and increase line failure probability. The methodology identifies the best combination of upgrades (new lines, hardening existing lines, and placing switching devices). Methodologically, we propose a two-stage distributionally robust planning optimization problem with DDU that considers the distribution system's multiperiod operation. The first stage determines optimal switching actions and line investments, and the second stage evaluates the worst-case expected operational cost under a DDU framework designed to account for the endogenous impact of power-flow levels and hardening investment decisions in the line failure probabilities. An iterative method is tailored to handle the problem and numerical experiments demonstrate a more prepared grid to deal with wildfire risk.

Power systems investment planning↗
DOE OSTI2021

A Rapid Decision Support Tool for Estimating Impacts of a Vadose Zone Volatile Organic Compound Source on Groundwater and Soil Gas

Diminishing rates of subsurface volatile contaminant removal by soil vapor extraction (SVE) oftentimes warrants an in‐depth performance assessment to guide remedy decision‐making processes. Such a performance assessment must include quantitative approaches to better understand the impact of remaining vadose zone contamination on soil gas and groundwater concentrations. The spreadsheet‐based Soil Vapor Extraction Endstate Tool (SVEET) software functionality has recently been expanded to facilitate quantitative performance assessments. The updated version, referred to as SVEET2, includes expansion of the input parameter ranges for describing a site (site geometry, source characteristics, etc.), an expanded list of contaminants, and incorporation of elements of the Vapor Intrusion Estimation Tool for Unsaturated‐zone Sources software to provide soil gas concentration estimates for use in vapor intrusion evaluation. As part of the update, SVEET2 was used to estimate the impact of a tetrachloroethene (PCE) vadose zone source on groundwater concentrations, comparing SVEET2 results to field‐observed values at an undisclosed site where SVE was recently terminated. PCE concentrations from three separate monitoring wells were estimated by SVEET2 to be within the range of 6.0–6.7 μg/L, as compared to actual field concentrations that ranged from 3 to 11 μg/L PCE. These data demonstrate that SVEET2 can rapidly provide representative quantitative estimates of impacts from a vadose zone contaminant source at field sites. Finally, in the context of the SVE performance assessment, such quantitative estimates provide a basis to support remedial and/or regulatory decisions regarding the continued need for vadose zone volatile organic compound remediation or technical justification for SVE termination, which can significantly reduce the cost to complete for a site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

The perspective awareness model - Eliciting multiple perspectives to formulate high quality decisions

A great deal of attention is given to the importance of communication in environmental remediation and radioactive waste management. However, very little attention is given to eliciting multiple perspectives so as to formulate high quality decisions. Plans that are based on a limited number of perspectives tend to be narrowly focused whereas those that are based on a wide variety of perspectives tend to be comprehensive, higher quality, and more apt to be put into application. In addition, existing methods of dialogue have built-in limitations in that they typically draw from the predominant thinking patterns which focus in some areas but ignore others. This can result in clarity but a lack of comprehensiveness. This paper presents a Perspective Awareness Model which helps groups such as partnering teams, interagency teams, steering committees, and working groups elicit a wide net of perspectives and viewpoints. The paper begins by describing five factors that makes cooperation among such groups challenging. Next, a Perspective Awareness Model that makes it possible to manage these five factors is presented. The two primary components of this model --- the eight 'Thinking Directions' and the 'Shared Documentation' --- are described in detail. Several examples are given to illustrate how the Perspective Awareness Model can be used to elicit multiple perspectives to formulate high quality decisions in the area of environmental remediation and radioactive waste management. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

A behavior and physiology-based decision support tool to predict thermal comfort and stress in non-pregnant, mid-gestation, and late-gestation sows

Background: Although thermal indices have been proposed for swine, none to our knowledge differentiate by reproductive stage or predict thermal comfort using behavioral and physiological data. The study objective was to develop a behavior and physiology-based decision support tool to predict thermal comfort and stress in multiparous (3.28 ± 0.81) non-pregnant (n = 11), mid-gestation (n = 13), and late-gestation (n = 12) sows. Results: Regression analyses were performed using PROC MIXED in SAS 9.4 to determine the optimal environmental indicator [dry bulb temperature (T DB ) and dew point] of heat stress (HS) in non-pregnant, mid-gestation, and late-gestation sows with respiration rate (RR) and body temperature (T B ) successively used as the dependent variable in a cubic function. A linear relationship was observed for skin temperature (T S ) indicating that TDB rather than the sow HS response impacted TS and so TS was excluded from further analyses. Reproductive stage was significant for all analyses (P < 0.05). Heat stress thresholds for each reproductive stage were calculated using the inflections points of RR for mild HS and T B for moderate and severe HS. Mild HS inflection points differed for non-pregnant, mid-gestation, and late gestation sows and occurred at 25.5, 25.1, and 24.0 °C, respectively. Moderate HS inflection points differed for non-pregnant, mid-gestation, and late gestation sows and occurred at 28.1, 27.8, and 25.5 °C, respectively. Severe HS inflection points were similar for non-pregnant and mid-gestation sows (32.9 °C) but differed for late-gestation sows (30.8 °C). These data were integrated with previously collected behavioral thermal preference data to estimate the T DB that non-pregnant, mid-gestation, and late-gestation sows found to be cool (T DB < T DB preference range), comfortable (T DB = T DB preference range), and warm (T DB preference range < T DB < mild HS). Conclusions: The results of this study provide valuable information about thermal comfort and thermal stress thresholds in sows at three reproductive stages. The development of a behavior and physiology-based decision support tool to predict thermal comfort and stress in non-pregnant, mid-gestation, and late-gestation sows is expected to provide swine producers with a more accurate means of managing sow environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Wildfire management decisions outweigh mechanical treatment as the keystone to forest landscape adaptation

Modern land management faces unprecedented uncertainty regarding future climates, novel disturbance regimes, and unanticipated ecological feedbacks. Mitigating this uncertainty requires a cohesive landscape management strategy that utilizes multiple methods to optimize benefits while hedging risks amidst uncertain futures. We used a process-based landscape simulation model (LANDIS-II) to forecast forest management, growth, climate effects, and future wildfire dynamics, and we distilled results using a decision support tool allowing us to examine tradeoffs between alternative management strategies. We developed plausible future management scenarios based on factorial combinations of restoration-oriented thinning prescriptions, prescribed fire, and wildland fire use. Results were assessed continuously for a 100-year simulation period, which provided a unique assessment of tradeoffs and benefits among seven primary topics representing social, ecological, and economic aspects of resilience. Projected climatic changes had a substantial impact on modeled wildfire activity. In the Wildfire Only scenario (no treatments, but including active wildfire and climate change), we observed an upwards inflection point in area burned around mid-century (2060) that had detrimental impacts on total landscape carbon storage. While simulated mechanical treatments (~ 3% area per year) reduced the incidence of high-severity fire, it did not eliminate this inflection completely. Scenarios involving wildland fire use resulted in greater reductions in high-severity fire and a more linear trend in cumulative area burned. Mechanical treatments were beneficial for subtopics under the economic topic given their positive financial return on investment, while wildland fire use scenarios were better for ecological subtopics, primarily due to a greater reduction in high-severity fire. Benefits among the social subtopics were mixed, reflecting the inevitability of tradeoffs in landscapes that we rely on for diverse and countervailing ecosystem services. This study provides evidence that optimal future scenarios will involve a mix of active and passive management strategies, allowing different management tactics to coexist within and among ownerships classes. Our results also emphasize the importance of wildfire management decisions as central to building more robust and resilient future landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation

This is a presentation on the Cutting Edge Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation by the University of Utah, presented by No'am Zach Dvory. This video slide presentation, by the University of Utah, discussed the technical objectives of developing a real-time decision-making platform to enhance seismic monitoring and risk management during stimulation activities. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 15, 2024.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Corrective Action Decision Document/Closure Report for Corrective Action Unit 576: Miscellaneous Radiological Sites and Debris Nevada National Security Site, Nevada, Revision 0 with ROTCs 1-2

This Corrective Action Decision Document/Closure Report presents information supporting the closure of Corrective Action Unit (CAU) 576: Miscellaneous Radiological Sites and Debris, Nevada National Security Site, Nevada. This document complies with the requirements of the Federal Facility Agreement and Consent Order (FFACO) that was agreed to by the State of Nevada; U.S. Department of Energy (DOE), Environmental Management (EM); U.S. Department of Defense; and DOE, Legacy Management. The purpose of this Corrective Action Decision Document/Closure Report is to provide justification and documentation supporting the recommendation that no further corrective action is needed for CAU 576 based on the implementation of the corrective actions listed in the document.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

REopt: Energy Decision Analysis

REopt transforms complex energy project decisions into actionable results for building owners, utilities, and industry. Based on decades of NREL decision-support expertise, REopt guides investment in economic, resilient energy technologies. This presentation provides an overview of how REopt can help building owners, utilities, developers, and industry optimize the economic and resilience benefits of distributed energy resources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

USAID Energy Storage Decision Guide for Policymakers

The purpose of this report is to arm relevant decision makers with the initial layer of information they need to understand energy storage and to make informed policy, regulatory, and investment decisions around grid-connected energy storage. While many of the case studies presented in this report are based on experiences from the U.S. and Europe, the lessons learned can be applied to power sectors in emerging economies. Importantly, this report covers topics related grid-connected energy storage for power sector applications. The term “grid-connected” implies that the storage system is interconnected to a centralized power system. Topics related to off-grid, micro-grid and mini-grid energy storage applications are not covered in this report, nor are procurement practices for energy storage.

25 ENERGY STORAGE↗