Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “time minimization”

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.

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

At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Impact of Synthetic Parameters on Structure and Electrochemistry of High-Entropy Layered Oxide LiNi 0.2 Co 0.2 Mn 0.2 Al 0.2 Fe 0.2 O 2

Here, this study explored a high-entropy layered oxide (HELO), LiNi 0.2 Co 0.2 Mn 0.2 Al 0.2 Fe 0.2 O 2 , prepared by coprecipitation followed by heat treatment. Coprecipitation yielded a kinetically favored product, and the subsequent heat treatment under various temperatures and times allowed tuning the material toward more thermodynamically favored structures. Refinement of X-ray powder diffraction (XRD) revealed that after 450 °C treatment, ~12% of the Ni 2+ in the structure was located within the lithium cation layer. After heat treatment at 600, 700, and 800 °C, there was a continued decrease of Ni 2+ in the lithium cation layer to 9.3, 6.3, and 3.7%, respectively. Longer heat treatment times at 800 °C decreased the level to 2.5%. Electrochemical behavior was evaluated by cyclic voltammetry, galvanostatic cycling, rate capability testing, and electrochemical impedance spectroscopy, where increased loaded voltage, functional capacity, rate capability, and decreased impedance were observed for samples treated at higher temperatures with lower cation mixing. X-ray absorption near edge spectroscopy (XANES) data indicated that the redox activity of Ni and Co was dominant in the electrochemistry, while the participation of Mn or Fe was minimal. The level of Ni oxidation state change between charge and discharge related to the heat treatment temperature where the samples with high cation mixing showed lower capacity consistent with some Ni 3+ in the transition metal layer inaccessible for electron transfer. Longer heat treatment times at 800 °C did not continue to provide a benefit in electrochemical function even with some additional reduction in cation mixing.

25 ENERGY STORAGE↗
DOE OSTI2019

CT urography: how to optimize the technique

Purpose: Computed tomography urography (CTU) has emerged as the modality of choice for imaging the urinary tract within the past few decades. It is a powerful tool that enables detailed anatomic evaluation of the urinary tract in order to identify primary urothelial malignancies, benign urinary tract conditions, and associated abdominopelvic pathologies. As such, there have been extensive efforts to optimize CTU protocol. Methods: This article reviews the published literature on CTU protocol optimization, including contrast bolus timing, dose reduction, reconstruction algorithms, and ancillary practices. Conclusion: There have been many advances in CTU techniques, which allow for imaging diagnosis of a wide spectrum of diseases while minimizing radiation dose and maximizing urinary tract distension and opacification.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Hot Hydrogen Exposure of U x Zr 1-x C y Nuclear Fuel: The Influence of Composition and Density

Refractory carbide nuclear fuel has been one of the most promising fuel candidates for space nuclear propulsion due to its high melting point, temperature stability, and compatibility in a hot hydrogen environment. In this study, U x Zr 1-x C y fuel was produced by means of a carbothermic reduction process in different UC compositions including 5,10, 20, and 30 at.% UC in the fuel compound. The powder feedstock was consolidated via direct current sintering with densities up to 97% of the theoretical density. The samples with different U x Zr 1-x C y compositions were exposed to hot hydrogen at 2600 K for a cumulative time of 300 min. The samples were characterized by SEM, XRD, density, and measured for mass losses. The high-density samples displayed improved performance in hot hydrogen by minimizing porous sites and reducing areas of direct contact with hydrogen gas, leading to reduced mass losses. Variations in sample density proved to induce large changes in mass loss rates, increasing them up to 90%. The compositions with higher UC content reported the largest mass losses in the study. The loss of uranium occurred primarily at the surfaces exposed to the hot hydrogen where changes in the lattice constant confirmed losses exceeding 50% of the initial UC content in higher compositions, specifically to U 0.3 Zr 0.7 C y . XRD analyses revealed the presence of UH 3 in U 0.3 Zr 0.7 C y suggesting that metallic uranium formed inside the sample as a product of carbon losses. High-density U x Zr x-1 C y fuel with UC concentrations at or below 20 at.% UC exhibited stability and negligible density changes in a high temperature hydrogen environment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Prospects and Limitations of Predicting Fuel Ignition Properties from Low-Temperature Speciation Data

Using chemical kinetic modeling and statistical analysis, we investigate the possibility of correlating key chemical “markers”–typically small molecules–formed during very lean (φ ~ 0.001) oxidation experiments with near-stoichiometric (φ ~ 1) fuel ignition properties. One goal of this work is to evaluate the feasibility of designing a fuel-screening platform, based on small laboratory reactors that operate at low temperatures and use minimal fuel volume. Buras et al. [Combust. Flame2020,216, 472–484] have shown that convolutional neural net (CNN) fitting can be used to correlate first-stage ignition delay times (IDTs) with OH/HO2 measurements during very lean oxidation in low-T flow reactors with better than factor-of-2 accuracy. In this work, we test the limits of applying this correlation-based approach to predict the low-temperature heat release (LTHR) and total IDT, including the sensitivity of total IDT to the equivalence ratio, φ. We demonstrate that first-stage IDT can be reliably correlated with very lean oxidation measurements using compressed sensing (CS), which is simpler to implement than CNN fitting. LTHR can also be predicted via CS analysis, although the correlation quality is somewhat lower than for first-stage IDT. In contrast, the accuracy of total IDT prediction at φ = 1 is significantly lower (within a factor of 4 or worse). Furthermore, these results can be rationalized by the fact that the first-stage IDT and LTHR are primarily determined by low-temperature chemistry, whereas total IDT depends on low-, intermediate-, and high-temperature chemistry. Oxidation reactions are most important at low temperatures, and therefore, measurements of universal molecular markers of oxidation do not capture the full chemical complexity required to accurately predict the total IDT even at a single equivalence ratio. As a result, we find that φ-sensitivity of ignition delay cannot be predicted at all using solely correlation with lean low-T chemical speciation measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Regulating hydrogel mechanical properties with an electric field

Stimuli-responsive polymeric materials have attracted significant attention due to their ability to change properties in response to various external stimuli. Using an electric field as the stimulus is of particular interest as it possesses the potential for seamless integration of materials with electronic systems. While many materials with electric field responsive actuation have an associated mechanical property change, it is beneficial to develop materials that exhibit mechanical property changes without accompanying significant shape deformation. To address this challenge, here we designed a semi-interpenetrating polymer network (semi-IPN) hydrogel system containing both polyelectrolytes and salt ions, which enables electric field induced changes in mechanical properties while minimizing actuation. We first successfully verified the viability of our design by removing salt ions through a diffusion-only method where we witnessed the stiffness increased to 4.5 times the initial value while still being highly deformable. After this, we applied an electric field to transport the salt ions out of the hydrogel, as shown by both Raman spectroscopy and scanning electron microscopy. We were able to show a time-dependent stiffness increase, the maximum of which was 5 times the original stiffness. We quantified ion transport and water-splitting in the hydrogel by both experiments and simulations. Following this, we showed functional system reversibility by reversing the direction of the current to reinject salt ions into the semi-IPN hydrogel and reducing its stiffness to below the initial value. It's worth noting that our simulations enable us to understand the governing mechanisms behind ion generation and salt transport that leads to mechanical property changes. Finally, we were able to fabricate a spatially variable stiffness haptic interface with our hydrogel, with demonstrated reversibility and cyclability. This research can possibly find applications in soft robotics and haptics and also inspire the development of bio-compatible electronics related devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Steering an intense relativistic electron beam in a linear induction accelerator

The best electron beam transport through a linear induction accelerator (LIA) is achieved when the beam is well centered on the magnetic axis of the focusing solenoids. Since the beam may be injected offset from, or at an angle to, the centerline, dipole magnets are usually provided as a means to steer the beam and center it. Steering may be accomplished by trial and error, but this is very time consuming, especially for accelerators with a low repetition rate for beam position measurements and dipole adjustments. With this in mind, this article presents a steering method requiring a minimal number of measurements and adjustments to position the beam at any desired location, including positioning on the centerline.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A parametric SPICE model for the simulation of spark gap switches

The use of SPICE-based software for the simulation of pulsed power systems—even large complex systems—has become commonplace in the pulsed power community. This is in contrast to earlier work in the field that relied on specially developed simulation codes such as Sandia’s Screamer or the Navy Research Lab’s Bertha, which natively incorporated models for common pulsed power components such as spark gap switches. Unlike these programs, SPICE programs provide a simple and familiar user interface and wide availability. However, SPICE programs do not include realistic models for key pulsed power circuit devices—including the spark gap switch. While simple switch models do exist in SPICE programs, these can only crudely approximate the behavior of a spark gap. This effort focuses on developing an SPICE circuit model for a gas-filled spark gap switch that is physically realistic while being simple enough to permit simulations to run in reasonable times on typical personal computers. Detailed information is provided for implementation in two common versions of SPICE: LTspice and Orcad PSPICE. Adaptation to other SPICE programs is possible with minimal modification. The model is intended as a design tool that uses physical parameters as inputs to connect it directly to the development of useable pulsed power systems. Data collected from the operation of a high-pressure pulsed-charged switch and a complete 12-stage Marx generator have been used to demonstrate the implementation and accuracy of the model over a wide range of parameters.

Pouncey, J. Cameron (ORCID:0000000153500816)↗
DOE OSTI2021

Realistic inflation in no-scale U(1) R symmetric flipped SU(5)

We have realized non-minimal Higgs inflation and standard hybrid inflation in the supersymmetric flipped SU(5) model with U(1) R symmetry using the no-scale form of the Kähler potential. In non-minimal Higgs inflation the waterfall Higgs field plays the role of inflaton, and in standard hybrid inflation the gauge singlet field S is employed as an inflaton. The predictions of both models are in good agreement with the Planck 2018 data. For numerical calculations we have fixed the gauge symmetry breaking scale, M, around 2 × 10 16 GeV. In both models the inflaton field values are constrained below m P . The tensor to scalar ratio r in non-minimal inflation is of the order of 10 -3 and for standard hybrid inflation r is tiny, of order 10 -15 –10 -4 . The scalar spectral index in both cases lie within the Planck 1-σ bounds, and the running of the scalar spectral index lies in the range, -dn s /d ln k ~ 6 × 10 -4 for non-minimal model and 10 -9 –10 -3 for the standard hybrid model. A realistic scenario of reheating and non-thermal leptogenesis is employed with reheat temperature T r ~ 10 9 GeV for non-minimal model and 10 6 –10 10 GeV for standard hybrid model. The R-symmetry plays a vital role in forbidding rapid proton decay, but at the same time it also suppresses terms responsible for generating right handed neutrino masses. A realistic scenario of right handed neutrino masses is obtained by considering effective R symmetry breaking at the nonrenormalizable level with adequate suppression of rapid proton decay.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Exploring the fusion power plant design space: comparative analysis of positive and negative triangularity tokamaks through optimization

The optimal configuration choice between positive triangularity (PT) and negative triangularity (NT) tokamaks for fusion power plants hinges on navigating different operational constraints rather than achieving specific plasma performance metrics. This study presents a systematic comparison using constrained multi-objective optimization with the integrated FUsion Synthesis Engine (FUSE) framework. Over 200 000 integrated design evaluations were performed exploring the trade-offs between capital cost minimization and operational reliability (maximizing q 95 ) while satisfying engineering constraints including 250 ± 50 MW net electric power, tritium breeding ratio > 1.1, power exhaust limits and an hour flattop time. Both configurations achieve similar cost-performance Pareto fronts through contrasting design philosophies. PT, while demonstrating resilience to pedestal degradation (compensating for up to 40% reduction), are constrained to larger machines (R 0 > 6.5 m) by the narrow operational window between L–H threshold requirements and the research-established power exhaust limit (P sol /R < 15 MW m –1 ). This forces optimization through comparatively reduced magnetic field (∼8 T). NT configurations exploit their freedom from these constraints to access compact, high-field designs (R 0 ~ 5.5 m, B 0 >12 T), creating natural synergy with advancing HTS technology. Sensitivity analyses reveal that PT’s economic viability depends critically on uncertainties in L–H threshold scaling and power handling limits. Notably, a 50% variation in either could eliminate viable designs or enable access to the compact design space. These results suggest configuration selection should be risk-informed: PT offers the lowest-cost path when operational constraints can be confidently predicted, while NT is robust to large variations in constraints and physics uncertainties.

FUSE framework↗
DOE OSTI2022

Accumulator Sizing for the Hybrid Hydraulic Electric Architecture (HHEA) Using Dynamic Programming

Abstract The Hybrid Hydraulic Electric Architecture (HHEA) is an approach to electrifying and improving that does not require very large electric machines. The majority power is provided hydraulically via a set of common pressure rails while small electric machines are used to modulate that power to meet exact demand. Each common pressure rail has an accumulator, which keeps the pressure of each rail near constant as long as the volume in the accumulator does not change much. A main pump adds or removes fluid from each accumulator as needed to reduce volume changes in the accumulators. It is the operation of this main pump which is investigated here. In previous analysis it was assumed that the size of the accumulators was large enough to account for any difference in fluid volume without significantly changing the pressure. In this paper, the required accumulator sizes are studied using a dynamic programming approach. At each time step the inlet and outlet of the main pump could be connected to any of the common pressure rails. These decisions for the main pump were optimized to minimize the required accumulator size. Case studies are conducted using drive cycles from a 22-ton excavator, a 20-ton wheel loader and a 5-ton excavator. The machines could be operated with total accumulator sizes of less than 20, 10, and 5 liters respectively. Required accumulator size was found to vary with pump flow rate, the frequency at which the pump/motor was able to change operating conditions, the tolerance level of pressure deviation and the accumulator’s polytropic index.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Two-Level Sketching Alternating Anderson Acceleration for Complex Physics Applications

We present a novel two-level sketching extension of the Alternating Anderson–Picard (AAP) method for accelerating fixed-point iterations in challenging single- and multiphysics simulations governed by discretized PDEs. Our approach combines a static, physics-based projection that reduces the least-squares (LS) problem to the most informative field (e.g., via Schur-complement insight) with a dynamic, algebraic sketching stage driven by a backward stability analysis under Lipschitz continuity. We introduce inexpensive estimators for stability thresholds and cache-aware randomized selection strategies to balance computational cost against memory access overhead. The resulting algorithm solves reduced LS systems in place, minimizes memory footprints, and seamlessly alternates between low-cost Picard updates and Anderson mixing. Implemented in Julia, our two-level sketching AAP achieves up to 50% time-to-solution reductions compared to standard Anderson acceleration—without degrading convergence rates—on benchmark problems including Stokes, 𝑝-Laplacian, bidomain, and Navier–Stokes formulations at varying problem sizes. These results demonstrate the method’s robustness, scalability, and potential for integration into high-performance scientific computing frameworks. Our implementation is available open source in the AAP.jl library.

Barnafi, Nicolas [University of Chile, Santiago]↗
DOE OSTI2024

Markov Decision Processes for Intelligent, Risk-Informed Asset-Management Decision-Making

Advanced nuclear reactors are a promising option for aiding the world in achieving its net-zero carbon emission goals, however, there are significant challenges to attaining and maintaining economic competitiveness with other sources of electricity. To improve the economic competitiveness of advanced reactor designs, a project was initiated to explore the use of Markov Decision Processes (MDPs) to guide asset-management decision-making during advanced reactor operation. MDPs are a powerful tool for optimizing decision-making in complex environments and their application to advanced reactors can aid in planning maintenance and repair activities to minimize downtime and maximize generation. The described approach expands on previous work regarding the use of MDPs for operational decision-making through the direct incorporation of real-time plant information. The integral MDP analysis includes information from online component diagnostic tools and the plant’s real-time generation risk assessment (GRA) and probabilistic risk assessment (PRA), which evaluate plant risk from both an economic and safety perspective. The result is an asset-management optimization framework that is based on real-time data regarding plant component status and the current best-estimate of plant risk. The paper presents an overview of the theoretical framework to incorporate the different information pathways into an integral MDP analysis, along with example analyses.

Grabaskas, David↗
DOE OSTI2023

Molten Salt Sampling Techniques and Analytical Approaches

Recent global interest in pyroprocessing and molten salt reactors has brought salt sampling methods and techniques back to the forefront of nuclear safeguards concerns. Issues with uranium supplies have also encouraged various countries to pursue advanced nuclear fuel cycles. Tracking nuclear material in molten salt has proven to be a challenge and updating molten salt sampling will greatly help in this endeavor. Molten salt is problematic to sample due to salt stratification, lack of homogeneity, solids, and difficulty with hot cell adaptations. Various salt sampling techniques have been used since before the 1960s including surface, spoon/spatula, and bar solidification. Since then, new types of sampling techniques have been developed to improve sampling results. These include rod/dip, pipet, suction, filtered sampling along with devices such as the Valve Core Sampler and the Multi-Level Sampler. These different approaches are being analyzed and improved upon along with developing requirements for an improved salt sampling device. Work continues to develop salt samplers that are more robust, easier to segment, collect at a specific depth, can work with filters, and can collect fines. Sampling parameters are also being narrowed in terms of stirring, settling time, filtration, depth, etc. In the future, we hope to address deficiencies for process control and nuclear material accountancy control by determining the best way to collect samples that minimizes contaminants and is representative. A compilation of salt sampling approaches, analyses techniques, and an evaluation of findings will be presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

"Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed Autonomy Traffic"

This paper introduces a novel control framework for Lagrangian variable speed limits in hybrid traffic flow environments utilizing automated vehicles (AVs). The framework was validated using a fleet of 100 connected automated vehicles as part of the largest coordinated open-road test designed to smooth traffic flow. The framework includes two main components: a high-level controller deployed on the server side, named Speed Planner, and low-level controllers called vehicle controllers deployed on the vehicle side. The Speed Planner designs and updates target speeds for the vehicle controllers based on real-time Traffic State Estimation (TSE) [1]. The Speed Planner comprises two modules: a TSE enhancement module and a target speed design module. The TSE enhancement module is designed to minimize the effects of inherent latency in the received traffic information and to improve the spatial and temporal resolution of the input traffic data. The target speed design module generates target speed profiles with the goal of improving traffic flow. The vehicle controllers are designed to track the target speed meanwhile responding to the surrounding situation. The numerical simulation indicates the performance of the proposed method: the bottleneck throughput has increased by 5.01%, and the speed standard deviation has been reduced by a significant 34.36%. We further showcase an operational study with a description of how the controller was implemented on a field-test with 100 AVs and its comprehensive effects on the traffic flow.

Wang, Han↗
DOE OSTI2025

Small-scale production of bespoke accelerated aging plutonium alloy

Here, this study demonstrates the 100 g scale manufacture of a plutonium alloy that ages at an accelerated rate. The resulting alloy ages six times faster than typical weapons-grade plutonium due to the addition of 238 Pu. As a major innovation, the process involved using a partial direct oxide reduction technique. This method was achieved by developing a new, complex geometry stirrer using additive manufacturing to reduce the 238Pu oxide and efficiently incorporate it into weapons-grade plutonium metal. The material was then purified by molten salt extraction and electrorefining before being alloyed with gallium. The alloy was then cold-rolled and annealed in a homogenization heat treatment. The resulting disk was characterized by metallography and differential scanning calorimetry, and the impurity content was determined using analytical chemistry techniques. The results show that a homogeneous delta phase plutonium alloy was achieved with expected microstructure and minimal impurities. This study was also successful in changing the plutonium isotopic composition by incorporating additional 238 Pu to accelerate the effects of radiation damage. This enables researchers to study long-term aging phenomena in a reduced time frame, thus avoiding the need for large-scale material production and circumventing the limitations of using naturally aged, archived plutonium.

Aging theory↗
DOE OSTI2023

Real-time control of connected vehicles in signalized corridors using pseudospectral convex optimization

Recent advances in Connected and Automated Vehicle (CAV) technologies have opened up new opportunities to enable safe, efficient, and sustainable transportation systems. However, developing reliable and rapid speed control algorithms in highly dynamic environments with complex inter-vehicle interactions and nonlinear vehicle dynamics is still a daunting task. In this paper, we develop a novel speed control method for CAVs to produce optimal speed profiles that minimize the fuel consumption and avoid idling at signalized intersections. To this end, an optimal control problem is formulated using the information of the upcoming traffic signal to adapt vehicles' speeds to avoid frequent stop-and-go driving patterns. Here, by applying the pseudospectral discretization method and the sequential convex programming method, the computational efficiency is greatly improved, enabling potential real-time on-vehicle applications. In addition, the algorithm is implemented under a model predictive control framework to ensure online control with instant response for collision avoidance and robust vehicle coordination. The proposed algorithm is verified through numerical simulations of three different traffic scenarios. The convergence and accuracy of the proposed approach are demonstrated by comparing with a popular nonlinear solver. Furthermore, the benefit of the proposed method in both traffic mobility and fuel efficiency is validated using the speed profile determined from a traffic following model in a simulation software as the baseline.

42 ENGINEERING↗
DOE OSTI2022

Model-based reconstruction for enhanced x-ray CT of dense tri-structural isotropic particles

Tri-structural isotropic (TRISO) fuel particles are a key component of next generation nuclear fuels. Using x-ray computed tomography (CT) to characterize TRISO particles is challenging because of the strong attenuation of the x-ray beam by the uranium core, leading to severe photon starvation in a substantial fraction of the measurements. Furthermore, the overall acquisition time for a high-resolution CT scan can be very long when using conventional laboratory-based x-ray systems and reconstruction algorithms. Specifically, when analytic methods such as the Feldkamp–Davis–Kress (FDK) algorithm are used for reconstruction, it results in severe streak artifacts and noise in the corresponding 3D volume, which makes subsequent analysis of the particles challenging. In this paper, we develop and apply model-based image reconstruction (MBIR) algorithms to improve the quality of CT reconstructions for TRISO particles to facilitate better characterization. We demonstrate that the proposed MBIR algorithms can significantly suppress artifacts with minimal pre-processing compared to conventional approaches. We also demonstrate that the proposed MBIR approach can obtain high-quality reconstruction compared to the FDK approach even when using a fraction of the typically acquired measurements, thereby enabling dramatically faster measurement times for TRISO particles.

Venkatakrishnan, Singanallur↗
DOE OSTI2022

Probing Distinctive Redox Mechanism in Ni-Rich Cathode Via Real-Time Quick X-Ray Absorption Spectroscopy

X-ray radiation damage on the measuring system has been a critical issue regularly for a long-time exposure to X-ray beam during the in operando characterizations, which is particularly severe when the applied X-ray energy is near the absorption edges (M, L, K, etc.) of the interest element. Here, to minimize the negative effects raised by beam radiation, we employ quick X-ray absorption spectroscopy (QXAS) to study the electrochemical reaction mechanism of a Ni-rich layered structure cathode for lithium-ion batteries. With the advanced QXAS technique, the electronic structure and local coordination environment of the transition metals (TMs) are monitored in-operando with limited radiation damage. Compared to the conventional step-mode X-ray absorption spectroscopy, the QXAS can provide more reliable oxidation state change and more detailed local structure evolutions surrounding TMs (Ni and Co) in Ni-rich layered oxides. By leveraging these advantages of QXAS, we demonstrated that the Ni dominates the electrochemical process with the Co being almost electrochemically inactive. Reversible Ni ions movement between TMs sites and Li sites is also revealed by the time-resolved QXAS technique.

25 ENERGY STORAGE↗