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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Exploration of High Depth-to-Width Ratio Micro Friction Stir Welding on Thin 6061-T6 Aluminum Butt Joints

In the autogenous joining process of thin 6061-T6 aluminum plates, micro friction stir welding (μFSW) is employed to explore the limitations of high depth to width ratio (HDWR) welding. In this explorative study, 1.25mm plate is joined in a butt joint fashion, multiple HDWR μFSW tools are developed, and the welding parameters are optimized to create a DWR greater than 0.4. A proposed method of implementing induction preheating to the joint is presented and the subsequent characterization of the welds are discussed. Upon completion of the project, the limitations on HDWR μFSW will be more accurately defined, and the best weld will be characterized to determine some of metallurgical properties. This study further expands the operating window for autogenous welding with solid state processes on thin aluminum plate as well as highlight methods for process improvement for tooling design and pre-heating methods.

Shambaugh, Colton↗
DOE OSTI2026

Reference floating wind array designs for three representative regions

This work presents the systematic development of three open-source reference floating wind array designs. The designs are tailored to representative site conditions for three regions of the United States: Humboldt Bay off the coast of California, the Gulf of Maine, and the Gulf of America. We adopted existing reference designs for the individual 15 MW turbines, semisubmersible floating platforms, substations, mooring systems, and power cables – integrating and adapting them as needed for each location. We adapted existing dynamic cable designs to use larger conductor sizes to meet the arrays' power transmission requirements, and we set up redundant mooring systems for each substation. The layout of each array is a uniform-grid design optimized to approximately minimize the levelized cost of energy (LCOE) within a square lease area while satisfying spatial constraints. These constraints ensure adequate clearances between adjacent turbines and between underwater components during the layout optimization to prevent clashing and ensure that all components reside within the lease boundaries. Substations are included to allow accounting for intra-array cable costs. They are placed within the uniform grid to maintain the navigability of the arrays. For each feasible layout considered, annual energy production and cable routing costs are calculated and updated in the LCOE objective function. After the optimization, we refined the cable routing with a mix of algorithmic and manual methods to ensure that the cables avoid mooring system components and approach the substation with adequate clearances. We confirmed the suitability of each reference array's layout by comparing the wake losses at each wind heading angle to the wind rose, observing that the optimized layouts largely avoid wake losses in the predominant wind directions. These reference arrays provide open-source baseline designs to enable future research and innovation of floating wind technology at the array scale.

17 WIND ENERGY↗
DOE OSTI2025

Boosting Noise2Inverse via enhanced model selection for denoising computed tomography data

Synchrotron-based x-ray tomographic imaging enables the examination of the internal structure of materials at high spatial and temporal resolution. Experimental constraints can impose dose and time limits on the measurements, introducing a higher level of noise and artifacts in the reconstructed images. Deep learning has emerged as a powerful tool to remove noise from reconstructed images. Recently, the Noise2Inverse method was designed specifically for denoising reconstructed images without requiring paired noisy and clean images. This method creates multiple statistically independent reconstructions used to pair the data in which training involves transforming one reconstruction into the other, and vice versa. Originally designed to be used after a fixed number of epochs, we see in practice that this approach may not produce the optimal model and may unnecessarily waste computational resources. Therefore, we propose an alternative method of identifying the best model during training that aligns with the Noise2Inverse method. During validation, we compare the model output of the multiple reconstructions among each other. We hypothesize that the best model is the one that produces images with the highest similarity, implying a convergence in the predicted material properties and absorption values. To compare model outputs, we consider the absolute error, square error, structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and cosine similarity. We evaluate our method on two simulated tomography datasets and two, real-world, low-contrast, high-energy x-ray tomography datasets. We show our approach is more effective at determining the best model, up to an increase of 12.50% and 12.53% in SSIM and PSNR, respectively, while only requiring a fifth of the training time compared to the original approach.

CT↗
DOE OSTI2024

Synthesizing, Compounding, and Characterizing a Heat Labile Polyurethane Foam

ABSTRACT A need exists for a packaging foam material that can be converted from solid to gaseous degradation products at reasonably low energy levels or temperatures, such as 100O C. This paper will primarily discuss the approaches currently being used to synthesize and characterize such a material. These approaches include the incorporation of novel polyols such as azo containing diols, polycarbonate diols, and polypropylene carbonate polyols into polyurethane foams. Characterization methods include NMR, FTIR, TGA, finite element analysis, impact strength, and others. This project will be funded for a duration of three years. Year 1 focused on developing the proposed test methods and producing an initial rigid polyurethane foam. Year 2 focuses on refining the materials and test methods. If appropriate, design of experiment (doe) techniques will be used to optimize components, component levels, density and other variables to attain required final material properties (TGA weight loss, impact strength, etc.). Year 3 focuses on scaling up to larger engineering quantities. The application for this material is in load securement for transportation of low level radioactive waste materials within the US Department of Energy (DOE) complex. Foam in place process equipment and operators will be shielded using this novel method over current practice. Current practice can involve time consuming methods of load securement in low level radiation environments. This new technique would eliminate exposure time securing the load and greatly improve the As Low As Reasonably Attainable (ALARA) conditions. The objective is to progress to higher Technical Readiness Levels (TRL) and larger pilot scale quantities. This paper discusses methodologies and presents current results to date.

Kranjc, Mark D.↗
DOE OSTI2025

ARCS: Agentic Retrieval-Augmented Code Synthesis with Iterative Refinement

Agentic Retrieval-Augmented Code Synthesis with Iterative RefinementIn supercomputing, efficient and optimized code generation is essential to leverage high-performance systems effectively. We have developed Agentic Retrieval-Augmented Code Synthesis (ARCS), an advanced framework for accurate, robust, and efficient code generation, completion, and translation. ARCS integrates Retrieval-Augmented Generation (RAG) with Chain-of-Thought (CoT) reasoning to systematically break down and iteratively refine complex programming tasks. An agent-based RAG mechanism retrieves relevant code snippets, while real-time execution feedback drives the synthesis of candidate solutions. This process is formalized as a state-action search tree optimization, balancing code correctness with editing efficiency. Evaluations on the Geeks4Geeks and HumanEval benchmarks demonstrate that ARCS significantly outperforms traditional prompting methods in translation and generation quality. By enabling scalable and precise code synthesis, ARCS offers transformative potential for automating and optimizing code development in supercomputing applications, enhancing computational resource utilization

Bhattarai, Manish [Los Alamos National Labs]↗
DOE OSTI2024

Multi-objective optimization of PWR core design using NSGA-II in RAVEN’s optimization framework

Designing an PWR loading pattern is a combinatorial problem challenging to solve by brute force or traditional methods due to the sheer amount of possible combination, and constraints. Nature-inspired algorithms, such as the genetic algorithm, have demonstrated the potential to tackle this problem. The goal of this work was to improve and demonstrate the capabilities for constrained, multi-objective optimization (MOO) of loading patterns using NSGA-II in RAVEN’s optimization framework.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Hydrogen Analysis by Gas Chromatography–Mass Spectrometry

The detection of hydrogen in complex gas mixtures is essential for many applications. Conventional approaches such as gas chromatography (GC) with thermal conductivity detection (TCD) and residual gas analyzers (RGAs) face significant limitations: TCD exhibits poor response when helium is used as a carrier gas, whereas RGAs lack chromatographic separation, preventing reliable quantification of hydrogen because of interference from other species. Traditional GC methods rely on dual-column configurations with packed or molecular-sieve porous layer open tubular (PLOT) columns to separate hydrogen from O2, N2, CO, CO2, CH4, and other hydrocarbons, increasing system complexity and limiting compatibility with mass spectrometry (MS) detection. In this work, we developed and validated a robust GC–MS method capable of directly detecting and quantifying hydrogen using electron ionization (EI) without dopants, reagent gases, or ion–molecule reaction schemes. By integrating a modified EI source and a cryogenically cooled single capillary column configuration, we achieved baseline separation of hydrogen from all major permanent gases and hydrocarbons in a refinery gas mixture using helium as the carrier gas. The method demonstrated excellent linearity, high sensitivity, and exceptional reproducibility. Adjustable sample-loop volumes and split ratios enabled optimization of peak shape and signal-to-noise performance for trace-level and percent-level hydrogen concentrations. Beyond hydrogen quantitation, the method provides simultaneous compositional profiling of other gases in a mixture in a single run, making it valuable for a wide range of tasks.

Lobodin, Vlad [ORNL]↗
DOE OSTI2026

Growth of Low-Defect WSe 2 Film via High-Purity van der Waals Crystal Precursor

Two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) exhibit exceptional electrical and optical properties, empowering their promising prospects for future nanoelectronics. Despite major advances in n-type 2D semiconductors, the field has yet to synthesize high-mobility p-type 2D TMDs, in particular WSe 2 , and systematically query the influence of defects. In this study, we unveil the pivotal role of substitutional impurity defects vis-à-vis the precursor used and growth method employed in defining the quality of 2D p-type WSe 2 . Density functional theory calculations suggest the adverse effect of Fe-, Co-, Ni- and Si-substituted W impurity defects on the mobility of WSe 2 , whereas defects such as O-, S-substituted Se and Mo-substituted W pose negligible impact. Guided by the theory, we pinpoint van der Waals (vdW) crystals, commonly used in mechanical exfoliation, as the optimal precursor, and develop a facile vdW crystal physical vapor deposition (PVD) method to grow high-purity monolayer 2D WSe 2 film (VPVD-WSe 2 ) that is continuous across a centimeter scale. A suite of spectroscopies confirms the markedly reduced defect density of the as-synthesized WSe 2 compared to those by typical chemical vapor deposition methods, and by PVD with commercial or hydrothermal precursors. Scanning tunneling microscopy further evidence the ultralow substitutional impurity defect density of VPVD-WSe 2 , greatly outperforming the control samples and approaching the mechanically exfoliated counterparts. The VPVD-WSe 2 based field-effect transistors exhibit notable electrical performance with record-high field-effect hole mobility up to 112 cm 2 V –1 s –1 at room temperature, exceeding the best-reported monolayer WSe 2 synthesized by chemical vapor deposition and rivaling the mechanically exfoliated 2D WSe 2 flakes.

WSe2↗
DOE OSTI2024

Optimal environmental and economic performance trade-offs for fifth generation district heating and cooling network topologies with waste heat recovery

Network topology greatly influences both the economic and environmental performance of fifth generation district heating and cooling (5GDHC) systems. In this study the optimal trade-offs between the environmental and economic performance of 5GDHC network topologies for a five-building district with waste heat recovery were explored. A life cycle assessment method was used to calculate the total life cycle CO 2 emissions (LCCO2) associated with the installation and operation of various network topologies. Twelve months of empirical data from a data center cooling system were analyzed to assess its suitability for integration into a 5GDHC system. The most suitable method for utilizing this waste heat was selected based on the ambient loop warm pipe setpoint, waste heat temperature, and district energy system configuration. A multi-objective optimization algorithm was used to select the 5GDHC network topology that provided the optimal trade-off between LCCO2 and life cycle cost (LCC). A trade-off parameter was employed to weigh the importance of each objective in the selection process. The results showed waste heat from the data center was suitable for integration into the 5GDHC system due to its availability and consistent temperature profile. When return temperatures of 25 °C or higher were available from the liquid-cooled system, direct pre-heating of the ambient loop warm pipe was found to be the most effective waste heat integration method. The selection of the network topology that provided the optimal trade-off between LCCO2 and LCC (optimal trade-off topology) was highly dependent on factors such as fuel prices, CO 2 prices, electricity CO 2 emissions factors, availability of waste heat, embodied CO 2 emissions associated with network installation and network infrastructure costs. Optimal trade-off topologies produced substantial LCCO2 reductions relative to corresponding LCC increases. LCCO2 reduction to LCC increase ratios from 5.78 to 117.79 were identified with CO 2 offset costs ranging from 4.77 to 60.08 ($/tCO 2 e).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

An efficient level set method for tracking many materials

Here, we present an efficient level set method to track an arbitrary number of materials. The algorithm is optimal in the sense that it only needs to store a single unsigned distance-like function and a single integer indicator function, independent of the number of materials or distinct regions being tracked. Furthermore, for smooth velocity fields and smooth interface shape, arbitrarily high order solutions can be demonstrated. For interfaces that are or become kinked, the solution is limited to second-order convergence rates in the L 1 norm and first-order in the L ∞ norm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Accelerating Embedding Potential Optimization by Reconstructing the Pseudo-Valence Electron Density

Density functional embedding theory (DFET) enables use of electronic structure methods with higher accuracy than density functional theory in a local region, with applications thus far ranging from (photo/electro)catalysis to reactions in solution. DFET partitions a large collection of atoms into smaller groups that interact via a shared embedding (interaction) potential V emb , determined via functional optimization. The optimized effective potential (OEP) process used to optimize V emb is time-consuming and becomes a computational bottleneck due to sharp, oscillating features of V emb near nuclei. Here, similar to pseudopotential theory, by reconstructing electron densities used in the OEP process from smoother pseudo-valence-only (PVO) electron densities as proxies for total densities of the full system and subsystems, we can retain accuracy in the embedded electronic structure calculations while potentially reducing the overhead of V emb construction, within the projector augmented-wave (PAW) formalism. We explore three different chemical reactions as exemplars to test PVO–DFET, namely, H 2 dissociative adsorption on a Cu(111) surface, H 2 O adsorption on a Pt(111) surface, and aqueous [Ca 2+ –SO 4 2– ] ion-pair formation. The PVO approximation works well for all three systems with minimal loss of accuracy (∼10–70 meV error relative to the original exact-derivative (ED) approach) while accelerating V emb generation for the Cu and Pt systems respectively by 20× and 5×. Given proper numerical convergence parameters, the spatial distributions of differences between PVO- and ED-based V emb outside the core regions are small, explaining the exceptional agreement between the two approaches. Finally, we anticipate that this more efficient PVO–DFET approximation will be useful whenever computation of V emb is much more expensive than subsequent embedded high-level electron correlation calculations.

approximation↗
DOE OSTI2026

Non-Invasive Electrode Impedance Estimation for Optimized Charge Profile Parameterization of Lithium-Ion Batteries

This work presents a non-invasive method for parameterizing a physically motivated equivalent circuit model of lithium-ion batteries using operando electrochemical impedance spectroscopy and time-domain data. The proposed model consists exclusively of linear circuit elements, enabling computationally efficient simulation and real-time implementation on battery management system chips. By integrating frequency- and time-domain measurements, the model accurately estimates internal states such as the negative electrode potential, achieving a root mean square error of 12.3 mV during fast charging validation. Parameterization requires only rate tests with sinusoidal perturbations at three different ambient temperatures, making the approach experimentally accessible. The model reveals key insights into battery behavior, including rate-dependent overpotentials primarily governed by charge transfer kinetics at the positive electrode, and temperature-dependent impedance contributions from both charge transfer and solid-state diffusion processes. Validation using reference electrodes confirms the model’s ability to detect lithium plating onset and reproduce impedance behavior across a wide range of operating conditions. The approach enables in situ optimization of fast charging profiles and lays the foundation for future extensions incorporating aging effects and plating dynamics.

25 ENERGY STORAGE↗
DOE OSTI2025

Optimizing on-ramp merging for connected and automated vehicles: A hierarchical approach using deep reinforcement learning and optimal control

On-ramp merging for Connected and Automated Vehicles (CAVs) presents significant challenges in dynamic traffic environments. Traditional methods and recent learning-based approaches often fail to simultaneously address decision-making complexity and execution precision under fluctuating conditions. This study introduces a novel hierarchical framework that combines: (1) a high-level Deep Reinforcement Learning (DRL) module that coordinates merging sequences through Virtual Traffic Signals (VTS) with Yield/Green phases and (2) a low-level optimal controller generating collision-free speed trajectories via pseudospectral convex optimization. A convolutional autoencoder compresses high-dimensional traffic states to enhance responsiveness. Extensive simulations demonstrate a 12.5% improvement in mainline throughput a 28% reduction in emergency braking events, and 31.66% lower fuel consumption compared to baseline methods. Furthermore, the framework’s effectiveness in coordinating CAV merges highlights its potential for real-world deployment. Future work will extend validation to multi-lane scenarios with mixed traffic and large-scale multiple merging points.

Connected and automated vehicles↗
DOE OSTI2025

Rapid Screening of Single-Atom Catalyst Synthesis Conditions Using ToF-SIMS and Facet-Dependent Single-Crystal Substrates

Single-atom catalysts (SACs) offer superior catalytic performance compared to traditional nanoparticle catalysts but are challenging to develop because of the need for extensive optimization and specialized characterization techniques. Here, this study presents a rapid and versatile method for detecting synthesis conditions and elucidating deposition mechanisms of SACs on various substrates. By depositing active elements (Au, Cu, Ni and Rh) on facet-specific single-crystalline substrates (CeO 2 , TiO 2 , MgO and Al 2 O 3 ) and employing time-of-flight secondary ion mass spectroscopy (ToF-SIMS), we assessed facet-dependent deposition behaviors and identified optimal conditions for solution-based SAC synthesis. On CeO 2 and TiO 2 , we confirmed facet-dependent deposition, primarily influenced by oxygen vacancy density and photocatalytic activity, respectively. MgO exhibited the formation of metal oxide/hydroxide clusters for all active elements, and the degree of clustering for Cu and Ni was correlated with the facet hydrolysis susceptibility. Notably, Au and Rh deposition on MgO was facet-independent, attributed to the formation of hydroxide species in solution. Al 2 O 3 , due to its chemical stability and lack of surface defects, did not show active element deposition. This study not only provides a time and cost-efficient method for prescreening SAC synthesis conditions, but it also provides valuable insights into the various deposition mechanisms governing SAC formation on different substrates, paving the way for the rational design of tailored SACs for various catalytic applications.

ToF-SIMS↗
DOE OSTI2025

Advancing continuous enzymatic hydrolysis for improved biomass saccharification

Background: A deployable, continuous enzymatic hydrolysis (CEH) process can address cost and commercialization risks associated with second-generation (Gen2) biorefinery sugar/lignin/ethanol production while contributing to energy supply and security. Developments in commercial enzymatic hydrolysis formulations targeting Gen2 pretreated biomass such as deacetylated mechanically refined (DMR) biomass necessitate a reassessment of the existing hybrid simultaneous saccharification and fermentation (SSF) approach. Notably, the practice of "finishing hydrolysis" in SSF has become problematic with the introduction of oxidative enzymes, such as lytic polysaccharide monooxygenases (LPMOs), into commercial cellulase formulations as these require specific redox conditions and cofactor. Moreover, continuous SSF has not been demonstrated at commercial scale, limiting deployment and the associated economic benefits to farmers, producers, and support industries. Results: Continuous enzymatic hydrolysis (CEH) was demonstrated at bench scale to enable optimal saccharification performance of deacetylated mechanically refined (DMR) pretreated biomass. Diafiltration was demonstrated to retain pretreated biomass solids and enzymes for continuous reaction while removing solubilized product sugars in situ. A significant breakthrough afforded by the CEH process is its ability to achieve equivalent endpoint conversions with approximately 50% lower enzyme loading. Yields of glucose and xylose were increased ~ 15% and ~ 4%, respectively, over batch hydrolysis. Unlike SSF using yeast or Zymomonas, CEH allows precise optimization of pH, temperature, oxygen tension, LPMO mediator concentration, and removal of end-product inhibitors. Conclusions: Advanced CEH holds promise as a transformational, process-intensified, and cost-effective method for producing soluble clarified biomass sugars and insoluble lignin-rich streams. Enhancing saccharification performance, optimizing operating parameters, and employing membrane filtration will help overcome existing challenges and enable the efficient production of valuable biomaterials from lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2024

Enabling Ultra-Compact, Lightweight, Efficient, and Reliable 6.6 kW On-Board Bi-Directional Electric Vehicle Charger with Advanced Topology and Control

The research explored new topologies, control methods, mechanical integration, and thermal management methods for electric vehicle (EV) on-board chargers. The team investigated capacitor-based power conversion, leveraging the high energy densities inherent to capacitive energy storage compared to inductive methods. The proposed topologies simultaneously enabled high power density and high efficiency of the design. The proposed architecture was demonstrated in a 6.6 kW bi-directional charger prototype. The research pursued several directions to improve system performance. Innovative topologies were studied for both the main power conversion stage as well as the single-phase twice-line-frequency energy buffer. To ensure robust and efficient operation, new control methods were developed to integrate these two subsystems. To achieve high power density in the full system solution, the mechanical structure of the charger is highly optimized to maximally fill the converter box volume. In parallel with the mechanical design effort, the converter was packaged with high-performance cooling methods which removed heat from key areas of power dissipation in the converter. The thermal management system was optimized to minimize its weight and volume, ultimately motivating the design of a custom additively manufactured cold-plate. The full system achieves a peak power of 7 kW with less than 0.3% total harmonic distortion (THD) and greater than 0.994 power factor in power factor correction (PFC) operation, corresponding to a total box-volume power density of 47.9 kW/L and gravimetric power density of 24.6 W/g. The system achieves a peak efficiency of 98.9%, with 97.9% efficiency at maximum power.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Optimal operation of multi-plant steam district heating systems for enhanced efficiency and sustainability

Despite their crucial role in supplying heat and power to universities, industries, and healthcare facilities, many steam-based district heating systems rely on outdated control methods. Among these, multi-central plant districts are particularly challenging due to the complexities of coordinating multiple plants, optimizing load distributions, and managing system downtime. In response, new operational strategies are developed to enhance the efficiency and sustainability of steam districts while utilizing existing resources. These strategies include reducing plant operational pressure without compromising the reliable supply to buildings and optimizing load allocation across multiple plants. The load allocation considers boiler part-load efficiency, runtime, network losses, and building pressure set points, and is compared with traditional multi-boiler controls. To support this exploration, new dynamic Modelica models are developed. In addition, methods to reduce modeling complexities are incorporated, enhancing their suitability for practical applications. A holistic district-wide analysis using a real university case study demonstrates a 4.7% fuel savings by lowering boiler operational pressure from 900 kPa to 600 kPa, along with a 13.3% reduction in condensation losses across the distribution network. Furthermore, the load allocation approach results in a 13.1% reduction in fuel consumption during peak winter periods and 15.3% during shoulder periods, with corresponding decreases in carbon emissions and fuel costs. This approach can also save maintenance costs by reducing the boiler runtime by 49.6%. In conclusion, this research underscores the benefits of retrofitting aging steam district heating systems, offering immediate operational improvements by enhancing efficiency, meeting regulatory compliance, and extending infrastructure lifespans while delaying costly overhauls.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization

This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on prevalent applications in computational mechanics and design optimization. We leverage Matérn-type Gaussian random fields (GRFs) generated using the SPDE method to model aleatoric uncertainties, including environmental influences, variating material properties, and geometric ambiguities. Our focus lies on delivering practical GRF realizations that accurately capture imperfections and variations and understanding how they impact the predictions of computational models as well as the shape and topology of optimized designs. Here we describe a numerical algorithm based on solving a generalized SPDE to sample GRFs on arbitrary meshed domains. The algorithm leverages established techniques and integrates seamlessly with the open-source finite element library MFEM and associated scientific computing workflows, like those found in industrial and national laboratory settings. Our solver scales efficiently for large-scale problems and supports various domain types, including surfaces and embedded manifolds. We showcase its versatility through biomechanics and topology optimization applications, emphasizing the potential to influence these domains. The flexibility and efficiency of SPDE-based GRF generation empowers us to run large-scale optimization problems on 2D and 3D domains, including finding optimized designs on embedded surfaces, and to generate design features and topologies beyond the reach of conventional techniques. Moreover, these capabilities allow us to model and quantify geometric uncertainties on reconstructed submanifolds, such as the interpolated surfaces of cerebral aneurysms provided by postprocessing CT scans. In addition to offering benefits in these specific domains, the proposed techniques transcend specific applications and generalize to arbitrary forward and backward problems in uncertainty quantification involving finite elements.

97 MATHEMATICS AND COMPUTING↗