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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

SMARTER Rules-Based Distributed Deconfliction of ADMS Applications

A conceptual numerical methodology derived from Grid Architecture principles is introduced for deconflicting setpoints issued by multiple advanced distribution management system applications. The methodology applies technical, economic, environmental, and social rules to eliminate non-viable combinations. The concept of temporal equipment controls budgets is introduced to preserve the health of physical assets and avoid equipment damage through repeated controls cycling. The rules are combined with a multi-criteria decision-making framework to select a near-optimal set of deconflicted setpoints using a set of qualitative and quantitative decision criteria selected by the distribution system operator. Numerical results are demonstrated on the IEEE 123-bus test feeder for three competing applications. Three alternative distributed schemes are used to decompose the problem: by topological area, by phase, and fully decentralized. The fully decentralized implementation is shown to yield near-optimal deconfliction results with significantly reduced computational time.

Anderson, Alexander A.↗
DOE OSTI2015

A two-phase investment model for optimal allocation of phasor measurement units considering transmission switching

Ensuring the reliability of an electrical power system requires a wide-area monitoring and full observability of the state variables. Phasor measurement units (PMUs) collect in real time synchronized phasors of voltages and currents which are used for the observability of the power grid. Due to the considerable cost of installing PMUs, it is not possible to equip all buses with PMUs. In this paper, we propose an integer linear programming model to determine the optimal PMU placement plan in two investment phases. In the first phase, PMUs are installed to achieve full observability of the power grid whereas additional PMUs are installed in the second phase to guarantee the N - 1 observability of the power grid. The proposed model also accounts for transmission switching and single contingencies such as failure of a PMU or a transmission line. Results are provided on several IEEE test systems which show that our proposed approach is a promising enhancement to the methods available for the optimal placement of PMUs.

Phasor measurement unit↗
DOE OSTI2024

Sampling Size Optimization for Bioburden Density Estimation in Planetary Protection

Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. Precise estimation of bioburden - the total number of microbes in or on spacecraft hardware – and the bioburden density are of utmost importance for PP. Such estimation is the way concordance with requirements is demonstrated, and it is critical for quantifying the potential risk of inadvertently contaminating other planetary bodies. Although a suite of molecular techniques have been used to thoroughly characterize and profile the microbiome of various cleanroom environments and spacecraft, the gold standard remains the physical enumeration of microbes via culturing of samples directly taken from spacecraft and associated surfaces. However, due to technical, budgetary, and programmatic constraints, only a manageable portion (around 10%) of the entire spacecraft surface is directly sampled with cotton swabs or wipes. To generate the bioburden current best estimate (CBE) for components not directly verifiable, the accepted approach is to apply a NASA-defined bioburden estimate based on the components’ manufacturing or assembly environment. This approach utilizes a prespecified bioburden density estimation that applies a maximum value across the total surface area of the specified component. For hardware components that underwent similar assembly processes, an implied bioburden is adopted for all components, based on a direct verification of a representative component within the same lot. Once all components have a CBE, the bioburden estimates are generated. In previous publication [ 1], we have shown that statistical risks quantifying the accuracy of the estimates for sampled, prespecified, and implied components can be derived and ranked. For mean squared error (MSE) function, the risks are available analytically and hence a cost function can be obtained to optimize the risks with respect to the sampling area and sampling cost. Since the sampling area and sampling cost are two complimentary variables, their sum will have a well-defined minimum. This paper presents the multivariate optimization of the integrated risk of an empirical Bayes estimator to determine the optimal sampling schedule for a given number of components. It is assumed that given a number of components, N, the bioburden density for each component can either be sampled, implied, or prespecified. The multivariate optimization searches through different options to sample, imply or prespecify the bioburden density for a component, and account for the component’s surface area and cost of sampling. The idea of the optimization is based on the observation that the statistical risk of using an estimator is a monotonically decreasing function of the sampled area. The larger the sampled area, the lower the risk of using the estimator as the estimator becomes more and more accurate as the sampling area increases. On the other hand, the cost of sampling is monotonically increasing as the sampled surface grows. This makes the risk and total cost of sampling complimentary variables which can be counterbalanced to achieve an optimal overall value with respect to the sampled surface. In this paper, the integrated risk has been used to quantify the accuracy of the estimator. This risk has been selected because it depends on neither the true value of the parameter nor on the collected data. The cost of each sample was also available to obtain the total cost of sampling of N components. The paper will present the results based on computer-simulated data as well as the data collected during the InSight mission. The computer-simulated data have N components with randomly generated total areas and each component assigned to one of the three categories according to the method of estimating of bioburden density: sampled, implied, or prespecified. The cost of sampling is also available. The cost of sampling is estimated based on a cost model provided by the planetary protection group at JPL. For this paper, the overall cost was assumed to be a linear function of exposure. The optimization process finds the allocation of the components to the three categories that minimizes the tradeoff between integrated risk and total cost. For the InSight data, a set of components is selected representing all three categories, and optimization is performed to determine if the performed allocation was optimal or if a better allocation could have been obtained. To the best of our knowledge, this work is the first attempt not only perform an accurate estimation of bioburden density but also do it in an optimal way.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Identification of the optimal carbon fiber shape for cost-specific compressive performance

We report carbon fiber composites offer superior mechanical performance compared to nearly all other useful materials for the design of structures. However, for cost-driven industries, such as with the wind energy and vehicle industries, the cost of commercial carbon fiber materials is often prohibitive for their usage compared to alternatives. This paper develops an approach to optimize fiber geometries for use in carbon fiber reinforced polymers to increase the compressive strength per unit cost. Compressive strength is a composite property that depends on the fiber, matrix, and interface, and an exact analytic expression does not exist that can accurately represent these complicated relationships. The approach taken instead is to use a weighted summation between the fiber cross-sectional area moment of inertia and perimeter as a proxy for compressive strength, with different weightings explored within the paper. Analyses are performed to identify optimal fiber geometries that increase the cost-specific compressive strength based on various assumptions and desired fiber volume fraction. Robust optimal shapes are identified which outperform circular fibers due to increases in area moment of inertia and perimeter, as well as decreases in carbon fiber processing costs.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Pumping Optimization Model for Pump and Treat Systems - 15091

Pump and Treat systems are being utilized to remediate contaminated groundwater in the Hanford 100 Areas adjacent to the Columbia River in Eastern Washington. Design of the systems was supported by a three-dimensional (3D) fate and transport model. This model provided sophisticated simulation capabilities but requires many hours to calculate results for each simulation considered. Many simulations are required to optimize system performance, so a two-dimensional (2D) model was created to reduce run time. The 2D model was developed as a equivalent-property version of the 3D model that derives boundary conditions and aquifer properties from the 3D model. It produces predictions that are very close to the 3D model predictions, allowing it to be used for comparative remedy analyses. Any potential system modifications identified by using the 2D version are verified for use by running the 3D model to confirm performance. The 2D model was incorporated into a comprehensive analysis system (the Pumping Optimization Model, POM) to simplify analysis of multiple simulations. It allows rapid turnaround by utilizing a graphical user interface that: 1 allows operators to create hypothetical scenarios for system operation, 2 feeds the input to the 2D fate and transport model, and 3 displays the scenario results to evaluate performance improvement. All of the above is accomplished within the user interface. Complex analyses can be completed within a few hours and multiple simulations can be compared side-by-side. The POM utilizes standard office computing equipment and established groundwater modeling software.

Baker, S.↗
DOE OSTI2015

Pumping optimization model for pump and treat systems - 15091

Pump and Treat systems are being utilized to remediate contaminated groundwater in the Hanford 100 Areas adjacent to the Columbia River in Eastern Washington. Design of the systems was supported by a three-dimensional (3D) fate and transport model. This model provided sophisticated simulation capabilities but requires many hours to calculate results for each simulation considered. Many simulations are required to optimize system performance, so a two-dimensional (2D) model was created to reduce run time. The 2D model was developed as a equivalent-property version of the 3D model that derives boundary conditions and aquifer properties from the 3D model. It produces predictions that are very close to the 3D model predictions, allowing it to be used for comparative remedy analyses. Any potential system modifications identified by using the 2D version are verified for use by running the 3D model to confirm performance. The 2D model was incorporated into a comprehensive analysis system (the Pumping Optimization Model, POM) to simplify analysis of multiple simulations. It allows rapid turnaround by utilizing a graphical user interface that: 1 allows operators to create hypothetical scenarios for system operation, 2 feeds the input to the 2D fate and transport model, and 3 displays the scenario results to evaluate performance improvement. All of the above is accomplished within the user interface. Complex analyses can be completed within a few hours and multiple simulations can be compared side-by-side. The POM utilizes standard office computing equipment and established groundwater modeling software. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Synthesis of Nickel-Doped Ceria Catalysts for Selective Acetylene Hydrogenation

Metallic nickel is known to be an active, but not a selective hydrogenation catalyst for conversion of alkynes to alkenes. On the other hand, nickel oxide is not active. Recently, we have demonstrated that nickel doped into ceria provides an inexpensive catalyst for selective hydrogenation of acetylene in the presence of ethylene. Here, we evaluate various synthesis methods to achieve optimal selective hydrogenation performance. We examined incipient wetness impregnation, coprecipitation, solution combustion, and sol-gel synthesis to study how the method of preparation affects catalytic structure and behavior. Sol-gel synthesis, coprecipitation, and solution combustion synthesis methods favor nickel incorporation into the ceria lattice, while incipient wetness impregnation creates segregated nickel species on the ceria surface. For hydrogenation of acetylene, these nickel surface species lead to poor ethylene selectivity due to ethane and oligomer formation. However, when nickel is incorporated into the ceria lattice, ethane formation is prevented even while achieving 100 % conversion of acetylene. Coke formation is also significantly reduced on these catalysts compared to conventional nanoparticle counterparts. Finally, we conclude that sol-gel synthesis provides the optimal method for creating a uniform dopant distribution within the high surface area ceria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

3D printing of anisotropic Sm–Fe–N nylon bonded permanent magnets

Abstract Fabricating a bonded magnet with a near‐net shape in suitable thermoplastic polymer binders is of paramount importance in the development of cost‐effective energy technologies. In this work, anisotropic Sm 2 Fe 17 N 3 (Sm–Fe–N) bonded magnets are additively printed using SmFeN anisotropic magnetic particles in a polymeric binder polyamide‐12 (PA12). The anisotropic SmFeN bonded magnets are fabricated by Big Area Additive Manufacturing followed by post‐printing alignment in a magnetic field. Optimal post‐alignment results in an enhanced remanence of ∼0.68 T in PA12 reflected in a parallel‐oriented (aligned) measured direction. The maximum energy product achieved for the additively printed anisotropic bonded magnet of Sm–Fe–N in PA12 polymer is 78.8 KJ m −3 . Our results show advanced processing flexibility with 3D printing of the development of SmFeN nylon bonded magnets designed for applications with no critical rare earth magnets.

42 ENGINEERING↗
DOE OSTI2019

Differentiation of pancreatic neuroendocrine tumors from pancreas renal cell carcinoma metastases on CT using qualitative and quantitative features

Purpose: To assess qualitative and quantitative imaging features on enhanced CT that may differentiate pancreatic neuroendocrine tumors (PNETs) from pancreatic renal cell carcinoma (RCC) metastases. Methods: This IRB-approved multi-center retrospective case–control study compared 43 resected PNETs and 28 resected RCC metastases with pre-operative enhanced CT identified consecutively between 2003 and 2017. Two blinded radiologists (R1/R2) independently assessed tumor location, attenuation (relative to pancreas), composition (solid/cystic/mixed), homogeneity (homogeneous/heterogeneous), calcification, multiplicity, and for main pancreatic duct (MPD) dilation. Tumors were segmented for quantitative texture analysis. Data were analyzed with Chi square, logistic regression, and receiver operating characteristic (ROC). Inter-observer agreement was assessed (Cohen’s kappa). Results: There was no difference in age, gender, location, attenuation, or composition (P > 0.05) between groups. PNETs were larger than RCC metastases (37 ± 23 mm vs. 26 ± 21 mm, P = 0.038), more frequently solitary (P < 0.001), subjectively more heterogeneous (P = 0.033/0.144, R1/R2), and associated with calcification (P = 0.002/0.004) and MPD dilation (P = 0.025/0.006). Agreement for subjective features was moderate-to-almost perfect (K = 0.4879–0.9481). Quantitative texture analysis showed higher entropy in PNETs (6.32 ± 0.49 versus 5.96 ± 0.53; P = 0.004) with no difference in other features studied (P > 0.05). Entropy had ROC area under the curve for diagnosis of PNET of 0.77 ± 0.06, with optimal sensitivity/specificity of 71.4/79.1%. Conclusions: Compared to pancreatic RCC metastases, PNETs are larger, more frequently solitary, contain calcification, show MPD dilation, and are subjectively and quantitatively more heterogeneous tumors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Multiphase computational fluid dynamics modeling of reacting flows in absorption columns for carbon capture

First-principles derived computational fluid dynamics (CFD) simulations have been proposed as a fundamental tool for investigating solvent-based CO 2 absorption in packed columns due to their ability to accurately represent the underlying nonlinear, multiscale dynamics. Numerous studies have previously utilized such CFD simulations to investigate hydrodynamics of columns with structured and random packings by assessing the key hydrodynamic metrics such as the interfacial and wetted areas. While mapping such metrics for different conditions is essential to the optimization of absorption columns, it is not sufficient, as the CO 2 capture rate depends also on the coupled, nonlinear dynamics from the underlying chemical reaction kinetics, thermodynamics, and heat-transfer rates. In this work, we present detailed CFD simulation results augmented by incorporating the effects of interfacial physical mass transfer of CO 2 , heat release from chemical reaction kinetics, and thermophysical property variations from resulting temperature gradients. We demonstrate the applicability of the proposed approach in numerically assessing the performance of packed columns by evaluating key hydrodynamic quantities, CO 2 absorption rates, and temperature rise in a reference column with packings that are structurally similar to the Sulzer Mellapak™ 250.Y packing, for different solvent inflow velocities and temperatures. Predictions from simulation results are found to be consistent with the trends in experimental observations from the literature, suggesting that the predictive capabilities of the simulation framework can be leveraged to guide the future development of absorber-column designs and optimized process flowsheets.

Absorption columns↗
DOE OSTI2021

Efficient kinetic thermal inverse modeling for organic material decomposition

The prevalent use of organic materials in manufacturing is a fire safety concern, and motivates the need for predictive thermal decomposition models. A critical component of predictive modeling is numerical inference of kinetic parameters from bench scale data. Currently, an active area of computational pyrolysis research focuses on identifying efficient, robust methods for optimization. This paper demonstrates that kinetic parameter calibration problems can successfully be solved using classical gradient-based optimization. We explore calibration examples that exhibit characteristics of concern: high nonlinearity, high dimensionality, complicated schemes, overlapping reactions, noisy data, and poor initial guesses. The examples demonstrate that a simple, non-invasive change to the problem formulation can simultaneously avoid local minima, avoid computation of derivative matrices, achieve a computational efficiency speedup of 10x, and make optimization robust to perturbations of parameter components. Techniques from the mathematical optimization and inverse problem communities are employed. By re-examining gradient-based algorithms, we highlight opportunities to develop kinetic parameter calibration methods that should outperform current methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Performance of a Cross-Flow Humidifier with a High Flux Water Vapor Transport Membrane

Water vapor transport (WVT) flux across a composite membrane that consists of a very thin perfluorosulfonic acid (PFSA) ionomer layer sandwiched between two expanded polytetrafluoroethylene (PTFE) microporous layers is investigated. Static and dynamic tests are conducted to measure WVT flux for different composite structures; a transport model shows that the underlying individual resistances for water diffusion in the gas phase and microporous and ionomer layers and for interfacial kinetics of water uptake at the ionomer surface are equally important under different conditions. A finite-difference model is formulated to determine water transport in a full-scale (2-m2 active membrane area) planar cross-flow humidifier module assembled using pleats of the optimized composite membrane. In agreement with the experimental data, the modeled WVT flux in the module increases at higher inlet relative humidity (RH) of the wet stream and at lower pressures, but the mass transfer effectiveness is higher at higher pressures. The model indicates that the WVT flux is highest under conditions that maintain the wet stream at close to 100% RH while preventing the dry stream from becoming saturated. The overall water transport is determined by the gradient in RH of the wet and dry streams but is also affected by vapor diffusion in the gas layer and the microporous layer.

combined thermal and mass transfer↗
DOE OSTI2016

MicroRaman measurements for nuclear fuel reprocessing applications

Treatment and reuse of used nuclear fuel is a key component in closing the nuclear fuel cycle. Solvent extraction reprocessing methods that have been developed contain various steps tailored to the separation of specific radionuclides, which are highly dependent upon solution properties. The instrumentation used to monitor these processes must be robust, require little or no maintenance, and be able to withstand harsh environments such as high radiation fields and aggressive chemical matrices. Our group has been investigating the use of optical spectroscopy for the on-line monitoring of actinides, lanthanides, and acid strength within fuel reprocessing streams. This paper will focus on the development and application of a new MicroRaman probe for on-line real-time monitoring of the U(VI)/nitrate ion/nitric acid in solutions relevant to used nuclear fuel reprocessing. Previous research has successfully demonstrated the applicability on the macroscopic scale, using sample probes requiring larger solution volumes. In an effort to minimize waste and reduce dose to personnel, we have modified this technique to allow measurement at the microfluidic scale using a Raman microprobe. Under the current sampling environment, Raman samples typically require upwards of 10 mL and larger. Using the new sampling system, we can sample volumes at 10 μL or less, which is a scale reduction of over 1,000 fold in sample size. Finally, this paper will summarize our current work in this area including: comparisons between the macroscopic and microscopic probes for detection limits, optimized channel focusing, and application in a flow cell with varying levels of HNO 3 , and UO 2 (NO 3 ) 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Exploring impacts of electricity tariff on charging infrastructure planning: An activity-based approach

In the past decade, electric vehicles (EVs) have gained popularity for their efficiency and environmental benefits. Advances in battery technology and charging equipment have yielded long-range EVs and fast-charging. However, many major cities lack adequate charging infrastructure for daily EV use. This study addresses this gap by integrating activity-based modeling, charging behavior simulation, and charging infrastructure optimization. The research utilizes the POLARIS agent-based transportation model to accurately capture user activities, trip patterns, and traffic flows. Additionally, the study investigates the impact of fixed and spatiotemporal electricity rate distributions on optimal charging infrastructure deployment. The framework is applied to the Chicago regional area network and analyzed under various EV ownership scenarios. Further, the results reveal significant impacts of the charging pricing strategy on user decision-making and charging demand distribution. There is also a need for consistent pricing policies in charging infrastructure planning and operational phases to avoid drops in service quality.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Optimization of municipal solid waste collection and transportation routes

Graphical abstract: Display Omitted - Highlights: • Profitable integrated solid waste management system. • Optimal municipal waste collection scheme between the sources and waste collection centres. • Optimal path calculation between waste collection centres and transfer stations. • Optimal waste routing between the transfer stations and processing plants. - Abstract: Optimization of municipal solid waste (MSW) collection and transportation through source separation becomes one of the major concerns in the MSW management system design, due to the fact that the existing MSW management systems suffer by the high collection and transportation cost. Generally, in a city different waste sources scatter throughout the city in heterogeneous way that increase waste collection and transportation cost in the waste management system. Therefore, a shortest waste collection and transportation strategy can effectively reduce waste collection and transportation cost. In this paper, we propose an optimal MSW collection and transportation scheme that focus on the problem of minimizing the length of each waste collection and transportation route. We first formulize the MSW collection and transportation problem into a mixed integer program. Moreover, we propose a heuristic solution for the waste collection and transportation problem that can provide an optimal way for waste collection and transportation. Extensive simulations and real testbed results show that the proposed solution can significantly improve the MSW performance. Results show that the proposed scheme is able to reduce more than 30% of the total waste collection path length.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Integration of Fullerenes as Electron Acceptors in 3D Graphene Networks: Enhanced Charge Transfer and Stability through Molecular Design

Here, we report a concept that allows the integration of the characteristic properties of [60]fullerene in 3D graphene networks. In these systems, graphene provides high electrical conductivity and surface area while fullerenes add high electron affinity. We use molecular design to optimize the interaction between 3D graphene networks and fullerenes, specifically in the context of stability and charge transfer in an electrochemical environment. We demonstrated that the capacity of the 3D graphene network is critcally improved upon the addition of C 60 and C 60 monoadducts by providing additional acceptor states in the form of low-lying lowest unoccupied molecular orbitals of C 60 and its derivative. Guided by experimental results and first-principles calculations, we synthesized and tested a C 60 monoadduct with increased stability by strengthening the 3D graphene–C 60 van-der-Waals interactions. The synthesis approach and stabilization strategy presented here is expected to benefit the integration of graphene–C 60 hybrid materials in solar cell and charge storage applications.

25 ENERGY STORAGE↗
DOE OSTI2012

Recent developments in the production of liquid fuels via catalytic conversion of microalgae: experiments and simulations

Due to continuing high demand, depletion of non-renewable resources and increasing concerns about climate change, the use of fossil fuel-derived transportation fuels faces relentless challenges both from a world markets and an environmental perspective. The production of renewable transportation fuel from microalgae continues to attract much attention because of its potential for fast growth rates, high oil content, ability to grow in unconventional scenarios, and inherent carbon neutrality. Moreover, the use of microalgae would minimize ‘‘food versus fuel’’ concerns associated with several biomass strategies, as microalgae do not compete with food crops in the food chain. This paper reviews the progress of recent research on the production of transportation fuels via homogeneous and heterogeneous catalytic conversions of microalgae. This review also describes the development of tools that may allow for a more fundamental understanding of catalyst selection and conversion processes using computational modelling. The catalytic conversion reaction pathways that have been investigated are fully discussed based on both experimental and theoretical approaches. Finally, this work makes several projections for the potential of various thermocatalytic pathways to produce alternative transportation fuels from algae, and identifies key areas where the authors feel that computational modelling should be directed to elucidate key information to optimize the process.

09 BIOMASS FUELS↗
DOE OSTI2015

Low-temperature capacitive sensor based on perovskite oxides

Energy, environmental and social issues drive towards the green political economy and the development of advanced technologies, promoting renewable energy sources, improving energy conversion efficiency and reducing exhaust gas emissions. The development of sustainable technologies requires strategic research in the area of gas sensors for monitoring air quality, controlling gas emissions and optimizing combustion processes. Solid state sensors are the most attractive one because of their simplicity in function, small size and low cost. The aim of this work is to synthetize and characterize strontium titanate and test its sensing performance. The prepared sensor device shows significant sensitivity and response rate at room-temperature. However, because of the low recovery rate, the regeneration of the sensor has to be made at high temperature for promoting the decomposition of the carbonates formed on the perovkite surface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗