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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Compressed optimization of device architectures

Recent advances in nanotechnology have enabled researchers to control individual quantum mechanical objects with unprecedented accuracy, opening the door for both quantum and extreme- scale conventional computation applications. As these devices become more complex, designing for facility of control becomes a daunting and computationally infeasible task. Here, motivated by ideas from compressed sensing, we introduce a protocol for the Compressed Optimization of Device Architectures (CODA). It leads naturally to a metric for benchmarking and optimizing device designs, as well as an automatic device control protocol that reduces the operational complexity required to achieve a particular output. Because this protocol is both experimentally and computationally efficient, it is readily extensible to large systems. For this paper, we demonstrate both the bench- marking and device control protocol components of CODA through examples of realistic simulations of electrostatic quantum dot devices, which are currently being developed experimentally for quantum computation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Development of Kinetic Mechanisms for Next-Generation Fuels and CFD Simulation of Advanced Combustion Engines

Predictive chemical kinetic models are needed to represent next-generation fuel components and their mixtures with conventional gasoline and diesel fuels. These kinetic models will allow the prediction of the effect of alternative fuel blends in CFD simulations of advanced spark-ignition and compression-ignition engines. Enabled by kinetic models, CFD simulations can be used to optimize fuel formulations for advanced combustion engines so that maximum engine efficiency, fossil fuel displacement goals, and low pollutant emission goals can be achieved.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Strategic Plan: Decrease Critical Minerals Waste Through Enabling Advanced Manufacturing Techniques

In this report we developed a strategic outlook derived from previous findings by our Phase-2 Scorecard Report and the Critical Mineral Evaluation Report. In addition, Phase 2 Materials Scorecards have been developed in 2022 to provide a detailed justification and traceability for the adoption of additively manufactured structural materials and ceramics for nuclear deployment. The report provides a strategic vision to harvest the benefits of reduced material and energy demands by enhanced deployment of advanced manufacturing in nuclear technology. The objective of this report is to address the needs for imminent experimental/computational studies to optimize the deployment of advanced manufacturing for its energy-, cost-, and critical materials saving potentials. We display what further actions are needed to minimize supply risks of critical minerals and to lower the economic vulnerability when implementing the additional nuclear capacity projected by 2050, in support of the U.S. goal of net-zero carbon emission. The critical minerals essential for Gen-IV nuclear technology show either low disruption potential (supply risks) combined with high economic vulnerability, such as: copper, nickel, and chromium; or low supply risks combined with medium economic vulnerability, such as: manganese, molybdenum, tungsten, vanadium, tantalum, and zirconium. Enhancements in quality and yield of critical mineral recycling and the recovery of critical minerals from solid and industrial waste streams are needed to enhance supply security for stainless-steel production and to shift the time to scarcity for society to future years.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Glass formulation and composition optimization with property models: A review

Abstract Glass is a versatile material with a remarkable history and many practical applications. It plays a critical role in our everyday lives, the advancement of science, and the development of many technologies. The Edisonian type trial‐and‐error method was commonly used for conventional design of glass compositions, which was time‐consuming and costly. With the urgent need to develop new glass compositions for technology applications rapidly, it has become necessary to develop precise property models with predictive powers using large databases and efficient formulation approaches. This paper reviews the design of glass compositions using these analytical and numerical models of composition–structure–property relations of glasses, some based on large databases and machine learning approaches. Aspects of data collection, model fitting, feature extraction, model evaluation, and uncertainty quantification will be covered. Furthermore, advances in the glass optimization framework and available tools are summarized with examples. The outlook and perspective for further glass property model development and formulation approaches are discussed.

Lu, Xiaonan↗
DOE OSTI2023

Cost Benefit Analyses through Integrated Online Monitoring and Diagnostics (Final Report)

The objective of this research is to improve the economic competitiveness of advanced reactors through the optimization of cost and plant performance, which can be achieved by coupling intelligent online monitoring with asset management decision-making. As advanced reactors are early in the development life-cycle, online monitoring systems and associated sensor networks can be incorporated directly into the design without constraints related to retrofitting and system upgrades

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗
DOE OSTI2018

Smart Grid-Enabled CVR: An Advanced Application for Distribution Management Systems

A multilevel, multitasking smart grid-enabled conservation of voltage reduction (CVR) control and optimization methodology is proposed for advanced distribution management system (ADMS) platforms. The first level deals with the centralized optimization of volt/VAR optimization (VVO) devices; the second-level is for voltage control in the local domain or decentralized control; and the third level assesses the energy savings and CVR factor.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Studies in pulse shape discrimination for an optimized ASIC design

The continued advancements of Silicon Photomultipliers (SiPMs) have made them viable photosensors for low recoil energy Pulse Shape Discrimination (PSD) between fast neutron and gamma interactions when coupled to an appropriate scintillator. At the same time, the large number of channels in a typical array calls for the development of low-cost and low-power electronics. A custom integrated circuit (ASIC) is an ideal solution for this purpose. To assess the requirements for such an ASIC, studies were performed using two scintillators, Stilbene and EJ-276, coupled to a 6 x 6 mm SiPM from Onsemi. We demonstrate that both scintillators are viable for performing PSD for interaction energies from 100 keV to several MeV while optimizing the integration periods used in the PSD metric. These measurements inform the design parameters of the ASIC under development.

Si-PMTs↗
DOE OSTI2021

Task Parallelism to Optimize Performance of Environmental Modeling Software

Climate modeling is an integral part of environmental research, from studying rare phenomena to predicting future climate trends. The need for more accurate models is only growing, but as climate modeling capabilities advance, existing workflows require optimization to recoup performance. A solution comes in the form of task parallelism, a novel programming capability that provides an opportunity for optimization at execution time by allowing tasks to be executed in parallel, reducing runtime significantly. Using Parsl, an intuitive and scalable parallel scripting library for Python, we implement task parallelism within support software to aid in the continuous advancement of climate modeling technology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Advanced Control Architecture and Sensor Information Development for Process Automation, Optimization, and Imaging of Chemical Looping Systems

The Syngas Chemical Looping (SCL) process developed at The Ohio State University (OSU) uses an iron-based oxygen carrier to convert syngas into high-purity hydrogen while simultaneously capturing carbon dioxide that is readily sequestrable. A 25 kWth sub-pilot unit was successfully demonstrated multiple times on the OSU Clean Coal Research Facility, and a 250 kWth – 3 MWth pilot demonstration unit has been designed and constructed at the National Carbon Capture Center (NCCC) in Wilsonville, Alabama. The focus of this project is to develop multiple technologies to automate the startup and shutdown of chemical looping system. Success of this project will propel the advanced carbon capture method toward commercialization, hence be disruptive to the fossil fuel and power industries. Advanced process automation control architecture and imaging and optimization sensor software were developed for OSU chemical looping process. A high-level controller (HLC) consisting of decision-making and controller-selection logic integrated with sliding mode controllers (SMCs) were developed to perform chemical looping process startup and shutdown. Babcock & Wilcox Power Generation Group’s FocalPoint Optimization System was implemented to optimize the process operating conditions. The process automation controller and optimization information were realized and tested on OSU’s existing sub-pilot chemical looping test unit under atmospheric condition. The implemented control architecture was able to perform the complete process procedure from startup, steady-state reaction operation to shutdown with minimal operator intervention. The controller was also implemented on the pressurized syngas chemical looping (SCL) pilot test unit constructed at the National Carbon Capture Center (NCCC), demonstrating its pressure control capability with a designed transient state trajectory. An electrical capacitance volume tomography (ECVT) sensor device and its software were developed to image the packed moving bed and slugging fluidized bed of oxygen carriers in chemical looping systems at elevated temperatures. The ECVT device constructed was capable of tracking the subtle voidage variance along the moving bed axis as a feature for directly measuring the oxygen carrier particles’ linear velocity. Also, the high temperature ECVT device was used to study the fluidization characteristics of Geldart Group D particles.

08 HYDROGEN↗
DOE OSTI2013

Optimization of stabilized leachate treatment using ozone/persulfate in the advanced oxidation process

Highlights: ► Ozone and persulfate reagent (O{sub 3}/S{sub 2}O{sub 8}{sup 2-}) was used to treat stabilized leachate. ► Central composite design (CCD) with response surface methodology (RSM) was applied. ► Operating variables including ozone and persulfate dosage, pH variance, and reaction time. ► Optimum removal of COD, color, and NH{sub 3}–N was 72%, 96%, and 76%, respectively. ► A good value of ozone consumption (OC) obtained with 0.60 (kg O{sub 3}/kg COD). - Abstract: The objective of this study was to investigate the performance of employing persulfate reagent in the advanced oxidation of ozone to treat stabilized landfill leachate in an ozone reactor. A central composite design (CCD) with response surface methodology (RSM) was applied to evaluate the relationships between operating variables, such as ozone and persulfate dosages, pH, and reaction time, to identify the optimum operating conditions. Quadratic models for the following four responses proved to be significant with very low probabilities (<0.0001): COD, color, NH{sub 3}–N, and ozone consumption (OC). The obtained optimum conditions included a reaction time of 210 min, 30 g/m{sup 3} ozone, 1 g/1 g COD{sub 0}/S{sub 2}O{sub 8}{sup 2-} ratio, and pH 10. The experimental results were corresponded well with predicted models (COD, color, and NH{sub 3}–N removal rates of 72%, 96%, and 76%, respectively, and 0.60 (kg O{sub 3}/kg COD OC). The results obtained in the stabilized leachate treatment were compared with those from other treatment processes, such as ozone only and persulfate S{sub 2}O{sub 8}{sup 2-} only, to evaluate its effectiveness. The combined method (i.e., O{sub 3}/S{sub 2}O{sub 8}{sup 2-}) achieved higher removal efficiencies for COD, color, and NH{sub 3}–N compared with other studied applications. Furthermore, the new method is more efficient than ozone/Fenton in advanced oxidation process in the treatment of the same studied leachate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Efficient Automated Driving Strategies Leveraging Anticipation and Optimal Control

Automated vehicles and advanced driver assistance systems bring computation, sensing, and communication technologies that exceed human abilities in some ways. For example, automated vehicles may sense a panorama all at once, do not suffer from human impairments and distractions, and could wirelessly communicate precise data with neighboring vehicles. Prototype and commercial deployments have demonstrated the capability to relieve human operators of some driving tasks up to and including fully autonomous taxi rides in some areas. The ultimate impact of this technology’s large-scale market penetration on energy efficiency remains unclear, with potential negative factors like road use by empty vehicles competing with positive ones like automatic eco-driving. Fundamentally enabled by historic and look-ahead data, this dissertation addresses the use of automated driving and driver assistance to optimize vehicle motion for energy efficiency. Facets of this problem include car following, co-optimized acceleration and lane change planning, and collaborative multi-agent guidance. Optimal control, especially model predictive control, is used extensively to improve energy efficiency while maintaining safe and timely driving via constraints. Techniques including chance constraints and mixed integer programming help overcome uncertainty and non-convexity challenges. Extensions of these techniques to tractor trailers on sloping roads are provided by making use of linear parameter-varying models. To approach the wheel-input energy eco-driving problem over generally shaped sloping roads with the computational potential for closed-loop implementation, a linear programming formulation is constructed. Distributed and collaborative techniques that enable connected and automated vehicles to accommodate their neighbors in traffic are also explored and compared to centralized control. Using simulations and vehicle-in-the-loop car following experiments, the proposed algorithms are benchmarked against others that do not make use of look-ahead information.

Dollar, Robert Austin↗
DOE OSTI2025

Stabilizing dynamic subsea power cables using Bi-stable nonlinear energy sinks

This study investigates vibration mitigation of dynamic subsea cables through passive bi-stable nonlinear energy sinks (B-NESs). These devices suppress vibration energy in a broadband way, and can be regarded as extensions of classical linear tuned mass dampers (TMDs) which are narrowband devices. Through the open-source MoorDyn library, we simulated the vibrations of a vertical subsea cable equipped with a set of B-NESs. Multi-objective optimization was performed to detect the B-NES parameters for optimal mitigation of the cable vibrations. Advanced signal processing verified the efficacy of the optimized B-NESs not only to rapidly absorb and locally dissipate vibration energy, but also to nonlinearly scatter vibration energy from low to high frequencies within the cable itself. This last feature is especially beneficial for vibration mitigation of the undersea cable, as at higher frequencies the cable vibrations exhibit drastically reduced amplitudes and are more effectively dissipated by inherent structural damping and hydrodynamic radiation damping. This contrasts with traditional TMDs which can mitigate vibration only at a single frequency. Furthermore, our robustness study confirms the B-NES's effectiveness under even varying environmental conditions. Overall, the B-NES's capacity for broadband vibration mitigation renders it a promising retrofit solution for improving the performance and operational safety of dynamic power cables in offshore wind farms and other marine applications.

17 WIND ENERGY↗
DOE OSTI2014

SU-F-BRF-11: Dose Rearrangement in High Dose Locally Advanced Lung Patients Based On Perfusion Imaging

Purpose: The use of mean lung dose (MLD) limits allows individualization of lung patient tumor doses at safe levels. However, MLD does not account for local lung function differences between patients, leading to toxicity variability at the same MLD. We investigated dose rearrangement to minimize dose to functional lung, as measured by perfusion SPECT, while maintaining target coverage and conventional MLD limits. Methods: Retrospective plans were optimized for 15 locally advanced NSCLC patients enrolled in a prospective imaging trial. A priority-based optimization system was used. The baseline priorities were (1) meet OAR dose constraints, (2) maximize target gEUD, and (3) minimize physical MLD. As a final step, normal tissue doses were minimized. To determine the benefit of rearranging dose using perfusion SPECT, plans were reoptimized to minimize functional lung gEUD as the 4th priority. Results: When only minimizing physical MLD, the functional lung gEUD was 10.8+/−5.0 Gy (4.3–19.8 Gy). Only 3/15 cases showed a decrease in functional lung gEUD of ≥4% when rearranging dose to minimize functional gEUD in the cost function (10.5+/−5.0 Gy range 4.3−19.7). Although OAR constraints were respected, the dose rearrangement resulted in ≥10% increases in gEUD to an OAR in 4/15 cases. Only slight reductions in functional lung gEUD were noted when omitting the minimization of physical MLD, suggesting that constraining the target gEUD minimizes the potential to redistribute dose. Conclusion: Prioritydriven optimization permits the generation of plans that respect traditional OAR limits and target coverage, but with the ability to rearrange dose based on functional imaging. The latter appears to be limited due to the decreased solution space when constraining target coverage. Since dose rearrangement may increase dose to other OARs, it is also worthwhile to investigate global biomarkers of lung toxicity to further individualize treatment in this population. Partially supported by R01-CA142840 and P01-CA59827.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-23: A Novel Two-Step Optimization Scheme for Tandem and Ovoid (T and O) HDR Brachytherapy Treatment for Locally Advanced Cervical Cancer

Purpose: To present a novel method allowing fast, true volumetric optimization of T and O HDR treatments and to quantify its benefits. Materials and Methods: 27 CT planning datasets and treatment plans from six consecutive cervical cancer patients treated with 4–5 intracavitary T and O insertions were used. Initial treatment plans were created with a goal of covering high risk (HR)-CTV with D90 > 90% and minimizing D2cc to rectum, bladder and sigmoid with manual optimization, approved and delivered. For the second step, each case was re-planned adding a new structure, created from the 100% prescription isodose line of the manually optimized plan to the existent physician delineated HR-CTV, rectum, bladder and sigmoid. New, more rigorous DVH constraints for the critical OARs were used for the optimization. D90 for the HR-CTV and D2cc for OARs were evaluated in both plans. Results: Two-step optimized plans had consistently smaller D2cc's for all three OARs while preserving good D90s for HR-CTV. On plans with “excellent” CTV coverage, average D90 of 96% (range 91–102), sigmoid D2cc was reduced on average by 37% (range 16–73), bladder by 28% (range 20–47) and rectum by 27% (range 15–45). Similar reductions were obtained on plans with “good” coverage, with an average D90 of 93% (range 90–99). For plans with inferior coverage, average D90 of 81%, an increase in coverage to 87% was achieved concurrently with D2cc reductions of 31%, 18% and 11% for sigmoid, bladder and rectum. Conclusions: A two-step DVH-based optimization can be added with minimal planning time increase, but with the potential of dramatic and systematic reductions of D2cc for OARs and in some cases with concurrent increases in target dose coverage. These single-fraction modifications would be magnified over the course of 4–5 intracavitary insertions and may have real clinical implications in terms of decreasing both acute and late toxicity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Advanced Transmission Technologies – GETs and HPCs Session 1: ATT Foundations and Dynamic Line Ratings (DLRs)

The INL TADA GETs Cohort Session 1, held on November 4, 2025, convened experts to address the integration of advanced transmission technologies, including Grid-Enhancing Technologies (GETs) and High Performance Conductors (HPCs), with a focus on digital assurance challenges. The session highlighted the growing importance of cybersecurity, supply chain transparency, reliability, and business risk management in deploying GETs, especially Dynamic Line Ratings (DLRs). Participants examined how expanded attack surfaces, limited vendor pools, and new regulatory requirements—such as FERC Orders 881, 2023, and 1920—are influencing utilities and technology providers. The workshop underscored the need for cyber-informed engineering, secure-by-design principles, and practical risk management strategies, while fostering collaboration and knowledge sharing among industry peers. Technical discussions covered the evolution from static to dynamic line ratings, complexities of cloud-based architectures, and NERC CIP compliance challenges. The session concluded with a collaborative risk exercise and a preview of future workshops on advanced power flow control and transmission topology optimization, reinforcing the cohort’s commitment to advancing digital assurance in the energy sector.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps

Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast irradiation case (Case II) solved with photon and electron modulated beams (IMRT + MERT); and a prostatic bed case (Case III) with a pronounced concave-shaped PTV by using volumetric modulated arc therapy. In the three cases, the required target prescription doses and constraints on organs at risk were fulfilled in a short enough time to allow routine clinical implementation. The quality assurance protocol followed to check CARMEN system showed a high agreement with the experimental measurements. Conclusions: A Monte Carlo treatment planning model exclusively based on maps performed from patient imaging data has been presented. The sequencing of these maps allows obtaining deliverable apertures which are weighted for modulation under a linear programming formulation. The model is able to solve complex radiotherapy treatments with high accuracy in an efficient computation time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Release on the Virtual Test Bed of a Molten Salt Reactor Experiment SAM-Pronghorn Coupled Model using the Domain Overlapping Approach

The nuclear industry is taking leaps in innovations with companies seeking a sustainable energy future through advanced nuclear reactors. The Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program seeks to substantiate and bolster the deployment of advanced reactors through flexible multifidelity, multiphysics simulations of advanced nuclear reactors. Applications like SAM for one-dimensional systems thermalhydraulics, and Pronghorn for multidimensional coarse mesh thermal-hydraulics, are geared to support innovations in industry by facilitating design, optimization, and licensing of advanced nuclear reactors. Coupling systems thermal-hydraulics and computational fluid dynamics codes can be difficult as the pressure coupling converges slowly; however, it is important to obtain the desired accuracy in each part of the primary loop. The authors of this model created an Overlapping-Domain Coupling (ODC) approach to coupling SAM and Pronghorn. Leveraging this coupling technique, a Molten Salt Reactor Experiment (MSRE) model was developed and released to the NEAMS/National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB). The MSRE was chosen to be modeled because of the wealth of experimental data available and because of the strong physics coupling between the core and primary circuit. This paper contextualizes the history of the MSRE, describes the thermal hydraulics models used, and detail the implementation of multidimensional thermal-hydraulics and system codes based on the ODC method for the MSRE model. Finally, this paper presents how other modelers could apply the SAM Pronghorn ODC for other advanced reactor models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗