SEARCH · Engineering Papers

Results for “Advanced Optimization”

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.

SourceResearch connectionFrom yearThrough year

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

At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Designing Advanced Electrolytes for High-Voltage High-Capacity Disordered Rocksalt Cathodes

Lithium (Li)-excess transition metal oxide materials which crystallize in the cation-disordered rock salt (DRX) structure are promising cathodes for realizing low-cost, high-energy-density Li batteries. However, the state-of-the-art electrolytes for Li-ion batteries cannot meet the high-voltage stability requirement for high-voltage DRX cathodes, thus new electrolytes are urgently demanded. It has been reported that the solvation structures and properties of the electrolytes critically influence the performance and stability of the batteries. In this study, the structure–property relationships of various electrolytes with different solvent-to-diluent ratios are systematically investigated through a combination of theoretical calculations and experimental tests and analyses. This approach guides the development of electrolytes with unique solvation structures and characteristics, exhibiting high voltage stability, and enhancing the formation of stable electrode/electrolyte interphases. These electrolytes enable the realization of Li||Li 1.094 Mn 0.676 Ti 0.228 O 2 (LMTO) DRX cells with improved performance compared to the conventional electrolyte. Specifically, Li||LMTO cells with the optimized advanced controlled-solvation electrolyte deliver higher specific capacity and longer cycle life compared to cells with the conventional electrolyte. Additionally, the investigation into the structure–property relationship provides a foundational basis for designing advanced electrolytes, which are crucial for the stable cycling of emerging high-voltage cathodes.

25 ENERGY STORAGE↗

DOE OSTI2022

Wood combustion nanoparticles emitted by conventional and advanced technology cordwood boilers, and their interactions in vitro with human lung epithelial monolayers

Biomass-burning boilers and stoves are widely used in many parts of the world, producing combustion emissions linked with health risks. Here, combustion emission nanoparticles (NPs) were collected from four representative wood burning boilers using oak cordwood at specific times in the burn cycle. The morphology and composition of the NPs was characterized using transmission electron microscopy and energy dispersive X-ray analysis. To determine the degree of NP cytotoxicity with human lung tissue, the combustion NPs were introduced to incubated lung bronchial epithelial monolayers (NCI-H292) in vitro at doses of 0.1×10 -6 and 3.0×10 -6 kg/L for 2 and 4 h. Histochemical analysis showed that cell death increased by a factor of 3.5 for both doses after 4 h when compared to the control. Ultrapure NPs prepared by wet chemical methods were also introduced to the epithelial lung cells for similar doses and exposure times and the cultures exhibited significantly reduced mortality. Electron microscopy was used to study the mechanism of cell mortality for the synthesized and combustion-based NPs by examining how the NP byproducts interacted with individual cell organelles. It was found that cell survival was strongly correlated with the absence of contaminants (salts, heavy metals, poly aromatic hydrocarbons) associated with the NPs entering the cells. Synthesized NPs consisting of pure carbon were relatively well tolerated and could be excreted without damaging the cell ultrastructure. Thus, careful removal of extraneous contaminants by controlling the burn cycle with a catalyst is essential to minimize the health and environmental effects of wood biofuel combustion. In better words, optimized advanced technology wood-burning boilers and stoves can provide a CO 2 -neutral energy source and significantly contribute to a future where fossil fuels have a reduced role.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Anisotropically Electrochemical-Mechanical Evolution in Solid-State Batteries and Interfacial Tailored Strategy

All-solid-state batteries have attracted attention owing to the potential high energy density and safety; however, little success has been made on practical applications of solid-state batteries, which is largely attributed to the solid–solid interface issues. A fundamental elucidation of electrode–electrolyte interface behaviors is of crucial significance but has proven difficult. The interfacial resistance and capacity fading issues in a solid-state battery were probed, revealing a heterogeneous phase transition evolution at solid–solid interfaces. The strain-induced interfacial change and the contact loss, as well as a dense metallic surface phase, deteriorate the electrochemical reaction in solid-state batteries. Furthermore, the in situ growth of electrolytes on secondary particles is proposed to fabricate robust solid–solid interface. Finally, our study enlightens new insights into the mechanism behind solid–solid interfacial reaction for optimizing advanced solid-state batteries.

25 ENERGY STORAGE↗

DOE OSTI2023

Model assessment of synthetic jets for turbulent combustion experiments

Abstract Understanding turbulent premixed flames is essential to predict and optimize advanced combustion strategies, but critical capability gaps exist for collecting and validating measurements such as turbulent flame speed. Here, we evaluate synthetic jets as a new, promising turbulence generation device for constant-volume combustion chambers, quantitatively assessing turbulence intensity and spatial uniformity in a hypothetical 4,189-cm 3 vessel for various premixture conditions. Graphic Abstract

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Sensor impacts on building and HVAC controls: A critical review for building energy performance

Building operations rely heavily on control systems and sensors. This paper provides a sophisticated literature review on sensor systems in building/HVAC systems, particularly in the context of controls, and their impacts on energy efficiency and thermal comfort. This study aims to understand the previous and current research and identify future research opportunities on this subject. The reviewed sensor systems were used for heuristic rule-based controls, local controls, and advanced optimal controls for existing and emerging technologies. Five major aspects of sensors are reviewed here: control loops for sensors, sensor types, sensor locations, sensor data, and a sensor impact evaluation framework. To augment the literature review, comprehensive standardized interviews were also conducted with relevant industry experts and practitioners. These interviews were designed and performed to (1) identify significant factors for selecting sensor sets and current undergoing issues, (2) identify potential improvements in sensor configuration/deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experiences to develop structured use-case scenarios. Researchers collected and analyzed 31 interview responses for this paper.

Building control↗

DOE OSTI2023

Silver-mediated separations: A comprehensive review on advancements of argentation chromatography, facilitated transport membranes, and solid-phase extraction techniques and their applications

The use of silver(I) ions in chemical separations, also known as argentation separations, is a powerful approach for the selective separation and analysis of many natural and synthetic organic compounds. In this review, a comprehensive discussion of the most common argentation separation techniques, including argentation-liquid chromatography (Ag-LC), argentation-gas chromatography (Ag-GC), argentation-facilitated transport membranes (Ag-FTMs), and argentation-solid phase extraction (Ag-SPE) is provided. For each of these techniques, notable advancements, optimized separations, and innovative applications are discussed. The review begins with an explanation of the fundamental chemistry underlying argentation separations, mainly the reversible π-complexation between silver(I) ions and carbon-carbon double bonds. Within Ag-LC, the use of silver(I) ions in thin-layer chromatography, high-performance liquid chromatography, as well as preparative LC are explored. This discussion focuses on how silver(I) ions are employed in the stationary and mobile phase to separate unsaturated compounds. For Ag-GC and Ag-FTMs, different silver compounds and supporting media are discussed, often with relation to olefin-paraffin separations. Ag-SPE has been widely employed for the selective extraction of unsaturated compounds from complex matrices in sample preparation. This comprehensive review of Ag-LC, Ag-GC, Ag-FTMs, and Ag-SPE techniques emphasizes the immense potential of argentation separations in separations science and serves as a valuable resource for researchers seeking to learn, optimize, and utilize argentation separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Peridynamics and surrogate modeling of pressure-driven well stimulation

In this work we use the peridynamics theory of solid mechanics to simulate fracture in an annular rock domain subject to an in-situ stress and create surrogate models that predict the area of the resulting cracks. Peridynamics is a non-local formulation of continuum mechanics that naturally accommodates material discontinuities. Furthermore, unlike other fracture modeling techniques there is no need to provide information about the crack path. We utilize the peridynamics code Peridigm and take a two-stage approach to fracture modeling. First an implicit solve is performed to compute the in-situ stress state. We then execute an explicit solve where a pressure loading designed to emulate fluid-driven hydraulic fracture is applied at the borehole and transmitted to the pre-stressed rock. We present results from polynomial and single and multi-level Gaussian process surrogate models constructed from a sampling study of the peridynamics model. The surrogates predict crack area given a measure of the in-situ stress anisotropy and rise time and amplitude of the pressure loading. These surrogates take a minuscule fraction of peridynamics model's running time to evaluate and are a step towards enabling advanced optimization and uncertainty quantification workflows that require many model evaluations.

42 ENGINEERING↗

DOE OSTI2024

Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions

Methane (CH 4 ) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH 4 fluxes is examined at 14 FLUXNET- CH 4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance-based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH 4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET-CH 4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Fast jet tagging with MLP-Mixers on FPGAs

We explore the innovative use of MLP-Mixer models for real-time jet tagging and establish their feasibility on resource-constrained hardware like FPGAs. MLP-Mixers excel in processing sequences of jet constituents, achieving state-of-the-art performance on datasets mimicking Large Hadron Collider conditions. By using advanced optimization techniques such as High-Granularity Quantization and Distributed Arithmetic, we achieve unprecedented efficiency. These models match or surpass the accuracy of previous architectures, reduce hardware resource usage by up to 97%, double the throughput, and half the latency. Additionally, non-permutation-invariant architectures enable smart feature prioritization and efficient FPGA deployment, setting a new benchmark for machine learning in real-time data processing at particle colliders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Designing Metabolic Division of Labor in Microbial Communities

ABSTRACT Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken” (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

SIRT-FILTER v1.0.0

Small Python package to compute tomographic reconstructions using a reconstruction method published in: Pelt, D.M., & De Andrade, V. (2017). Improved tomographic reconstruction of large-scale real-world data by filter optimization. Advanced Structural and Chemical Imaging 2: 17; and Pelt, D. M., & Batenburg, K. J. (2015). Accurately approximating algebraic tomographic reconstruction by filtered backprojection. In Proceedings of The 13th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (pp. 158-161).

PELT, DANIEL↗

DOE OSTI2016

High-Speed Multiplexed Spatiotemporally Resolved Measurements of Exhaust Gas Recirculation Dynamics in a Multi-Cylinder Engine Using Laser Absorption Spectroscopy

The need for more environmentally friendly and efficient energy conversion is of paramount importance in developing and designing next-generation internal combustion (IC) engines for transportation applications. One effective solution to reducing emissions of mono-nitrogen oxides (NO x ) is exhaust gas recirculation (EGR), which has been widely implemented in modern vehicles. However, cylinder-to-cylinder and cycle-to-cycle variations in the charge-gas uniformity can be a major barrier to optimum EGR implementation on multi-cylinder engines, and can limit performance, stability, and efficiency. Precise knowledge and fine control over the EGR system is thus crucial, particularly for optimizing advanced engine concepts such as reactivity controlled compression ignition (RCCI). An absorption-based laser diagnostic was developed to study spatiotemporal charge-gas distributions in an IC engine intake manifold in real-time. The laser was tuned to an absorption band of carbon dioxide (CO 2 ), a standard exhaust-gas marker, near 2.7 µm. The sensor was capable of probing four separate measurement locations simultaneously, and independently analyzing EGR fraction at speeds of 5 kHz (1.2 crank-angle degree (CAD) at 1 k RPM) or faster with high accuracy. Lastly, the probes were used to study spatiotemporal EGR non-uniformities in the intake manifold and ultimately promote the development of more efficient and higher performance engines.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2019

Trihalomethane precursor reactivity changes in drinking water treatment unit processes during a storm event

Source water quality can significantly impact the efficacy of water treatment unit processes and the formation of chlorinated and brominated trihalomethanes (THMs). Current water treatment plant performance models may not accurately capture how source water quality variations, such as organic matter variability, can impact treatment unit processes. To investigate these impacts, a field study was conducted wherein water samples were collected along the treatment train for 72 hours during a storm event. Systematic sampling and detailed analyses of water quality parameters, including non-purgeable organic carbon (NPOC), UV absorbance, and THM concentrations, as well as chlorine spiking experiments, reveal how the THM formation potential changes in response to treatment unit processes. Results show that the NPOC remaining after treatment has an increased reactivity towards forming THMs, and that brominated THMs form more readily than chlorinated counterparts in a competitive reaction. Thus both the reactivity and quantity of THM precursors must be considered to maintain compliance with drinking water standards, a finding that should be incorporated into the development of model-assisted treatment operation and optimization. Advanced granular activated carbon (GAC) treatment beyond conventional coagulation–flocculation–sedimentation processes may also be necessary to remove the surge loading of THM-formation precursors during a storm event.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Final technical report: SciDAC partnership "Predictive Computing for Condensed Matter"

Fundamental progress in energy technology depends critically on our ability to design, fabricate, characterize, and optimize advanced materials that can convert, transport, and store energies as well as display useful functions at minimum energy consumptions. To achieve this, we must first understand mechanisms underlying the functions and then be able to design materials with predicted properties. Unlike conventional structural materials, optoelectronic or magnetic materials for energy technology operate by quantum mechanical principles, which are hard to extract from experiments alone. Some representative unsolved problems of condensed-phase electronic structures in general include (1) the detailed mechanism of high-temperature superconductors such as cuprates and iron-arsenide materials; (2) the structures of solids in the presence of polymorphism; (3) excited states in solids and systematically accurate calculations of quasiparticle energy bands; (4) the structure of strongly correlated wave functions of solids. In this project, we aim at establishing general and predictive mathematical theories for solids and computational methods that implement them. We will then apply these methods to outstanding solid-state problems recognized by experimentalists including the above, with a view to solving them computationally. Hence, the project has the following three research objectives, all of which have been met: Predictive Electronic Structure Theories for Solids, Scalable Algorithms and Software, and Applications to Outstanding Condensed Matter Problems.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

TAO 3.10 Users Manual

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

TAO Users Manual (Rev. 3.15)

The Toolkit for Advanced Optimization (TAO) focuses on the development of algorithms and software for the solution of large-scale optimization problems on high-performance architectures. Areas of interest include unconstrained and bound-constrained optimization, nonlinear least squares problems, optimization problems with partial differential equation constraints, and variational inequalities and complementarity constraints. The development of TAO was motivated by the scattered support for parallel computations and the lack of reuse of external toolkits in current optimization software. Our aim is to produce high-quality optimization software for computing environments ranging from workstations and laptops to massively parallel high-performance architectures. Our design decisions are strongly motivated by the challenges inherent in the use of large-scale distributed memory architectures and the reality of working with large, often poorly structured legacy codes for specific applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

PETSc/TAO Users Manual: Revision 3.18

This manual describes the use of the Portable, Extensible Toolkit for Scientific Computation (PETSc) and the Toolkit for Advanced Optimization (TAO) for the numerical solution of partial differential equations and related problems on high-performance computers. PETSc/TAO is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all distributed memory communication.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗