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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Zigzag search for multi-objective optimization considering generation cost and emission

The zigzag search algorithm has been applied in engineering fields, such as oil well placement, with satisfactory results. Here, the zigzag search algorithm is introduced, modified with enhancement, and effectively applied to solve an economic emission dispatch problem and to demonstrate its practicability in power systems. The problem is formulated as a non-linear multi-objective optimization model taking energy constraints, generation limits, and transmission constraints into consideration. A set of non-dominant solutions can be obtained to form the Pareto front. Case studies are carried out with the IEEE 30-bus system and IEEE 118-bus system. The results indicate that the proposed zigzag search algorithms have the ability to deal with relevant power system problems. Comparisons are made with algorithms which have been widely used in literatures, such as the genetic algorithm (GA) and particle swarm optimization (PSO). Finally, this demonstrates that the zigzag search is easy to implement and is superior to other multi-objective (MO) techniques in both accuracy and efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Hybrid data-driven cement-stabilized soil design: An integration of machine learning, multi-objective optimization, and life cycle assessment

Soil stabilization is crucial in geotechnical engineering, yet conventional methods are often time-consuming, resource-intensive, and environmentally unsustainable. Despite growing interest in Machine Learning (ML) and optimization tools for mix design, few studies integrate these methods with decision-making techniques and environmental assessment to support practical implementation. This study proposes a hybrid data-driven framework for predicting strength, optimizing mix compositions, and evaluating environmental impacts via life cycle assessment of cement-stabilized soft soils. Six ML models were evaluated, and the top-performing eXtreme Gradient Boosting (XGB) model was further improved using the Grey Wolf Optimizer (GWO). The optimized XGB-GWO model, integrated with a polynomial cost function, served as the objective function in a multi-objective optimization problem solved via the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), with final mix selection guided by the entropy-weighted TOPSIS method. Validation through a case study produced mix designs offering superior strength-cost trade-offs, with the optimal mix achieving 2243.2 kPa unconfined compressive strength and a 16.07 % reduction in carbon emissions compared to the highest-cost design. In conclusion, this study offers a sustainable, scalable approach to soil stabilization and supports informed decision-making in construction.

Life cycle assessment↗
DOE OSTI2022

GenASiS Mathematics: Object-oriented manifolds, operations, and solvers for large-scale physics simulations (version 2)

We report GenASiS Mathematics provides modern Fortran classes furnishing extensible object-oriented functionality for the solution of fields governed by selected partial differential equations. The initial release included extensible object-oriented implementations of simple meshes and the evolution of generic conserved currents thereon. This revision - Version 2 of Mathematics - includes significant reorganization and streamlining of these classes, higher-order reconstruction by a different method, a Poisson solver, coarsening to avoid Courant time step limitations near coordinate singularities, and the offloading of computational kernels to GPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Optimizing fluvial flood mitigation strategies: A multi-objective approach for cost-effective and socially-aware infrastructure feasibility analysis

Effective levee planning must balance capital cost, risk reduction, and community priorities. These objectives are rarely optimized together. This study presents a feasibility phase, simulationin-the-loop framework that couples terrain-based flood modeling with a socially aware multiobjective optimizer. Flood risk is measured as Expected Annual Exposed Population (EAEP), obtained by integrating exposure over Annual Exceedance Probability (AEP) nodes, mirroring the Hydrologic Engineering Center's Flood Damage Reduction Analysis (HEC-FDA) expected-annual formulation but with people rather than dollars. Exposure per scenario is computed by overlaying binary inundation masks with a population surface at the tract level. Distributional fairness is encoded through a Group Benefit Share (GBS) constraint that requires high-SVI tracts to receive at least a baseline share of annualized benefits. Capital cost is represented by a height-dependent unit-cost model suitable for screening. This study addresses the two-objective problem, minimize cost and expected annual exposure subject to the GBS constraint, using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and leveraging Pareto front for feasibility phase decision making. Implemented with terrain-based flood modeling, GeoFlood, for rapid scenario evaluation, the framework is demonstrated in Southeast Texas. The results reveal clear trade-offs among cost, risk, and social benefits and identify non-dominated levee height configurations that satisfy the benefit-share floor. The contributions are a scalable decision support method that operationalizes expected annual population-based risk, embeds enforceable benefit-sharing guarantees, and uses lightweight simulation to explore large design spaces before higher fidelity design stages.

Flood mitigation↗
DOE OSTI2013

Comparisons of amine solvents for post-combustion CO{sub 2} capture: A multi-objective analysis approach

Amine solvents are of great interest for post-combustion CO{sub 2} capture applications. Although the development of new solvents is predominantly conducted at the laboratory scale, the ability to assess the performance of newly developed solvents at the process scale is crucial to identifying the best solvents for CO{sub 2} capture. In this work we present a methodology to evaluate and objectively compare the process performance of different solvents. We use Aspen Plus, with the electrolyte-NRTL thermodynamic model for the solvent CO{sub 2} interactions, coupled with a multi-objective genetic algorithm optimization to determine the best process design and operating conditions for each solvent. This ensures that the processes utilized for the comparison are those which are best suited for the specific solvent. We evaluate and compare the process performance of monoethanolamine (MEA), diethanolamine (DEA), and 2-amino-2-methyl-1-propanol (AMP) in a 90% CO{sub 2} capture process from a 550 MW coal fired power plant. From our analysis the best process specifications are amine specific and with those specific, optimized specifications DEA has the potential to be a better performing solvent than MEA, with a lower energy penalty and lower capital cost investment.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

A parallel variable population multi-objective optimizer for accelerator beam dynamics optimization

The simultaneous optimization of multiple objective functions is needed in many particle accelerator applications. In this paper, we present a parallel evolution based multi-objective optimizer that uses a variable population from generation to generation and an external storage to save good solutions. Two heuristic optimization methods, one uses the unified differential evolution and the other uses the real-coded genetic algorithm, are included in the optimizer to generate next generation candidate solutions, and are compared in the test examples. Finally, as an application, we applied this optimizer to the beam dynamics design optimization of a photoinjector and attained the optimal front solutions after 200 generations with the unified differential evolution offspring production scheme.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Optimizing and Exploring Untapped Micro-Hydro Hybrid Systems: a Multi-Objective Approach for Crystal Lake as a Large-Scale Energy Storage Solution

Increasing electricity demand and concerns about climate change and fossil fuel consumption have highlighted the importance of renewable energy resources and storage systems. This paper proposes a method for exploring untapped pumped hydro storage potentials to accommodate intermittent renewable energy generation profiles. Hourly measured data from 2022 in Benzie County, Michigan, United States, were gathered for system sizing and a thorough, realistic analysis. By employing the multi-objective grey wolf optimization algorithm, we formulated optimal sizing and energy-management strategies for three different scenarios. Unlike similar studies, the 3rd with triple objective functions (OFs) scenario aims to maximize both reliability and ecological OFs while minimizing the cost OF. It has shown promising results with multiple solutions, considering economic, environmental, and reliability factors. A case study conducted in Crystal Lake, Michigan, revealed that although Crystal Lake would function only as a micro-hydro power facility, it is a promising and huge storage unit with a substantial storage capacity of around 14.9734GWh. The system investigated is significant in the USA due to its rapid deployment capabilities, minimal construction requirements, and ease of integration with the distribution grid. The fuzzy logic method was employed to identify the best non-dominant solution among the other solutions. Furthermore, these outcomes include a notably low levelized cost of energy at 0.046147$/kWh, a robust index of reliability of 99.705%, and a significant reduction in CO₂ emissions amounting to 7.9142×10 3 tons/year, when considering the triple OFs. The paper’s methodology provides valuable insights for regions aiming to utilize renewable energy from untapped storage sources.

13 HYDRO ENERGY↗
DOE OSTI2023

Heavy-element production in a compact object merger observed by JWST

The mergers of binary compact objects such as neutron stars and black holes are of central interest to several areas of astrophysics, including as the progenitors of gamma-ray bursts (GRBs), sources of high-frequency gravitational waves (GWs) and likely production sites for heavy-element nucleosynthesis by means of rapid neutron capture (the r -process). Here we present observations of the exceptionally bright GRB 230307A. We show that GRB 230307A belongs to the class of long-duration GRBs associated with compact object mergers and contains a kilonova similar to AT2017gfo, associated with the GW merger GW170817. We obtained James Webb Space Telescope (JWST) mid-infrared imaging and spectroscopy 29 and 61 days after the burst. The spectroscopy shows an emission line at 2.15 microns, which we interpret as tellurium (atomic mass A = 130) and a very red source, emitting most of its light in the mid-infrared owing to the production of lanthanides. These observations demonstrate that nucleosynthesis in GRBs can create r -process elements across a broad atomic mass range and play a central role in heavy-element nucleosynthesis across the Universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗
DOE OSTI2012

Discovery of VHE γ -ray emission from the BL Lacertae object B3 2247+381 with the MAGIC telescopes

Here, we study the non-thermal jet emission of the BL Lac object B3 2247+381 during a high optical state. The MAGIC telescopes observed the source during 13 nights between September 30th and October 30th 2010, collecting a total of 14.2 h of good quality very high energy (VHE) γ-ray data. Simultaneous multiwavelength data was obtained with X-ray observations by the Swift satellite and optical R-band observations at the KVA-telescope. We also use high energy γ-ray (HE, 0.1-100 GeV) data from the Fermi satellite. We also dedected the BL Lac object B3 2247+381 (z = 0.119) , for the first time, at VHE γ-rays at a statistical significance of 5.6σ. A soft VHE spectrum with a photon index of -3.2 ± 0.6 was determined. No significant short term flux variations were found. Finally, we model the spectral energy distribution using a one-zone SSC-model, which can successfully describe our data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Recent developments in atomic/nuclear methodologies used for the study of cultural heritage objects

Archaeometry is an area established in the international community since the 60s, with extensive use of atomic-nuclear methods in the characterization of art, archaeological and cultural heritage objects in general. In Brazil, however, until the early '90s, employing methods of physics, only the area of archaeological dating was implemented. It was only after this period that Brazilian groups became involved in the characterization of archaeological and art objects with these methodologies. The Laboratory of Applied Nuclear Physics, State University of Londrina (LFNA/UEL) introduced, pioneered in 1994, Archaeometry and related issues among its priority lines of research, after a member of LFNA has been involved in 1992 with the possibilities of tomography in archaeometry, as well as the analysis of ancient bronzes by EDXRF. Since then, LFNA has been working with PXRF and Portable Raman in several museums in Brazil, in field studies of cave paintings and in the laboratory with material sent by archaeologists, as well as carrying out collaborative work with new groups that followed in this area. From 2003/2004 LAMFI/DFN/IFUSP and LIN/COPPE/UFRJ began to engage in the area, respectively with methodologies using ion beams and PXRF, then over time incorporating other techniques, followed later by other groups. Due to the growing number of laboratories and institutions/archaeologists/conservators interested in these applications, in may 2012 was created a network of available laboratories, based at http://www.dfn.if.usp.br/lapac. It will be presented a panel of recent developments and applications of these methodologies by national groups, as well as a sampling of what has been done by leading groups abroad.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

SIMULTANEOUS B'V'R' MONITORING OF BL LACERTAE OBJECT S5 0716+714 AND DETECTION OF INTER-BAND TIME DELAY

We present the results of our optical monitoring of the BL Lac object S5 0716+714 over seven nights in 2006 December. The monitoring was carried out simultaneously at three optical wavelengths with a novel photometric system. The object did not show large-amplitude internight variations during this period. Intranight variations were observed on four nights and probably on one more. Strong bluer-when-brighter chromatism was detected on both intranight and internight timescales. The intranight variation amplitude decreases in the wavelength sequence of B', R', and V'. Cross-correlation analyses revealed that the variability at the B' and V' bands leads that at the R' band by about 30 minutes on one night.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

VERITAS detection of γ-ray flaring activity from the BL LAC object 1ES 1727+502 during bright moonlight observations

During moonlit nights, observations with ground-based Cherenkov telescopes at very high energies (VHEs, E>100 GeV) are constrained since the photomultiplier tubes (PMTs) in the telescope camera are extremely sensitive to the background moonlight. Observations with the VERITAS telescopes in the standard configuration are performed only with a moon illumination less than 35% of full moon. Since 2012, the VERITAS collaboration has implemented a new observing mode under bright moonlight, by either reducing the voltage applied to the PMTs (reduced-high-voltage; RHV configuration), or by utilizing UV-transparent filters. While these operating modes result in lower sensitivity and increased energy thresholds, the extension of the available observing time is useful for monitoring variable sources such as blazars and sources requiring spectral measurements at the highest energies. In this paper we report the detection of γ-ray flaring activity from the BL Lac object 1ES 1727+502 during RHV observations. This detection represents the first evidence of VHE variability from this blazar. The integral flux is (1.1±0.2)×10{sup −11} cm{sup −2} s{sup −1} above 250 GeV, which is about five times higher than the low-flux state. The detection triggered additional VERITAS observations during standard dark-time. Multiwavelength observations with the FLWO 48″ telescope, and the Swift and Fermi satellites are presented and used to produce the first spectral energy distribution (SED) of this object during γ-ray flaring activity. The SED is then fitted with a standard synchrotron-self-Compton model, placing constraints on the properties of the emitting region and of the acceleration mechanism at the origin of the relativistic particle population in the jet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

QUANTITATIVE EVALUATION OF THE HYPOTHESIS THAT BL LACERTAE OBJECTS ARE QSO REMNANTS

We evaluate with numerical simulations the hypothesis that BL Lacertae objects (BLLs) are the remnants of quasi-stellar objects. This hypothesis is based on their highly peculiar redshift evolution. They have a comoving space density that increases with decreasing redshift, contrary to all other active galactic nuclei. We assume that relativistic jets are below detection in young radio-quiet quasars and increase in strength with cosmic time so that they eventually are detected as BLLs. Our numerical simulations fit very well the observed redshift distributions of BLLs. There are strong indications that only the high-synchrotron-peaked BLLs could be QSO remnants.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

G objects and primordial black holes

We suggest that "G objects" recently discovered in the Galactic Center may be clouds of gas bound by the gravitational field of stellar-mass black holes produced in the interactions of sublunar primordial black holes with neutron stars. If dark matter is composed of primordial black holes with masses (10 –16 –10 –10 )M ⊙ , these black holes can be captured by neutron stars in the Galactic Center, where the dark matter density is high. After the capture, the neutron star is consumed by the black hole, resulting in a population of (1–2)M ⊙ black holes. Furthermore, these stellar-mass black holes, accompanied by gaseous atmospheres, can account for the observed properties of the G objects, including their resilience to tidal disruption by the supermassive black hole in the Galactic Center while also producing emission consistent with inferred luminosities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Automated Vehicle Multi-Object Tracking at Scale with CAN

Millions of vehicles are on the road with RADAR sensors in use for adaptive cruise control (ACC), and RADAR sen- sors are not tracking all of the objects in the field of view. This work shows a work-in-progress tool to improve track- ing from RADAR and controller area network (CAN) which should be vitally useful for safety of transportation systems and automated vehicle development. The CAN data provides object detections, but there is a lingering data association problem. The contribution of this work in progress is the solution to the data association problem by posing the data association as a minimum cost network flow problem, and doing it at low cost with an eye toward scalable CPS research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Multi-Objective PMU Allocation for Resilient Power System Monitoring

Phasor measurement units (PMUs) enable better system monitoring and security enhancement in smart grids. In order to enhance power system resilience against outages and blackouts caused by extreme weather events or man-made attacks, it remains a major challenge to determine the optimal number and location of PMUs. In this paper, a multi-objective resilient PMU placement (MORPP) problem is formulated, and solved by a modified Teaching-Learning-Based optimization (MO-TLBO) algorithm. Three objectives are considered in the MORPP problem, minimizing the number of PMUs, maximizing the system observability, and minimizing the voltage stability index. The effectiveness of the proposed method is validated through testing on IEEE 14-bus, 30-bus, and 118-bus test systems. The advantage of the MO-TLBO-based MORPP is demonstrated through the comparison with other methods in the literature, in terms of iteration number, optimality and time of convergence.

Multi-Objective Optimization↗
DOE OSTI2022

High–throughput measurement of plant fitness traits with an object detection method using Faster R–CNN

Revealing the contributions of genes to plant phenotype is frequently challenging because loss-of-function effects may be subtle or masked by varying degrees of genetic redundancy. Such effects can potentially be detected by measuring plant fitness, which reflects the cumulative effects of genetic changes over the lifetime of a plant. However, fitness is challenging to measure accurately, particularly in species with high fecundity and relatively small propagule sizes such as Arabidopsis thaliana. An image segmentation-based method using the software ImageJ and an object detection-based method using the Faster Region-based Convolutional Neural Network (R-CNN) algorithm were used for measuring two Arabidopsis fitness traits: seed and fruit counts. The segmentation-based method was error-prone (correlation between true and predicted seed counts, r 2 = 0.849) because seeds touching each other were undercounted. By contrast, the object detection-based algorithm yielded near perfect seed counts (r 2 = 0.9996) and highly accurate fruit counts (r 2 = 0.980). Comparing seed counts for wild-type and 12 mutant lines revealed fitness effects for three genes; fruit counts revealed the same effects for two genes. Our study provides analysis pipelines and models to facilitate the investigation of Arabidopsis fitness traits and demonstrates the importance of examining fitness traits when studying gene functions.

59 BASIC BIOLOGICAL SCIENCES↗