SEARCH · Engineering Papers

Results for “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 1,729 records · Page 96

All sources NASA NTRS DOE OSTI

DOE OSTI2018

A Task-Optimized Neural Network Replicates Human Auditory Behavior, Predicts Brain Responses, and Reveals a Cortical Processing Hierarchy

A core goal of auditory neuroscience is to build quantitative models that predict cortical responses to natural sounds. Reasoning that a complete model of auditory cortex must solve ecologically relevant tasks, we optimized hierarchical neural networks for speech and music recognition. The best-performing network contained separate music and speech pathways following early shared processing, potentially replicating human cortical organization. The network performed both tasks as well as humans and exhibited human-like errors despite not being optimized to do so, suggesting common constraints on network and human performance. The network predicted fMRI voxel responses substantially better than traditional spectrotemporal filter models throughout auditory cortex. It also provided a quantitative signature of cortical representational hierarchy—primary and non-primary responses were best predicted by intermediate and late network layers, respectively. Here the results suggest that task optimization provides a powerful set of tools for modeling sensory systems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Optimization of cathodic arc deposition and pulsed plasma melting techniques for growing smooth superconducting Pb photoemissive films for SRF injectors

Superconducting photoinjectors have a potential to be the optimal solution for moderate and high current cw operating free electron lasers. For this application, a superconducting lead (Pb) cathode has been proposed to simplify the cathode integration into a 1.3 GHz, TESLA-type, 1.6-cell long purely superconducting gun cavity. In the proposed design, a lead film several micrometres thick is deposited onto a niobium plug attached to the cavity back wall. Traditional lead deposition techniques usually produce very non-uniform emission surfaces and often result in a poor adhesion of the layer. A pulsed plasma melting procedure reducing the non-uniformity of the lead photocathodes is presented. In order to determine the parameters optimal for this procedure, heat transfer from plasma to the film was first modelled to evaluate melting front penetration range and liquid state duration. The obtained results were verified by surface inspection of witness samples. The optimal procedure was used to prepare a photocathode plug, which was then tested in an electron gun. In conclusion, the quantum efficiency and the value of cavity quality factor have been found to satisfy the requirements for an injector of the European-XFEL facility.

42 ENGINEERING↗

DOE OSTI2023

Generalized method for the optimization of pulse shape discrimination parameters

Organic scintillators exhibit fast timing, high detection efficiency for fast neutrons and pulse shape discrimination (PSD) capability. PSD is essential in mixed radiation fields, where different types of radiation need to be detected and discriminated. In neutron measurements for nuclear security and non proliferation effective PSD is crucial, because a weak neutron signature needs to be detected in the presence of a strong gamma-ray background. Here, the most commonly used deterministic PSD technique is charge integration (CI). This method requires the optimization of specific parameters to obtain the best gamma-neutron separation. These parameters depend on the scintillating material and light readout device and typically require a lengthy optimization process and a calibration reference measurement with a mixed source. In this paper, we propose a new method based on the scintillation fluorescence physics that enables to find the optimum PSD integration gates using only a gamma-ray emitter. We demonstrate our method using three organic scintillation detectors: deuterated trans-stilbene, small-molecule organic glass, and EJ-309. In all the investigated cases, our method allowed finding the optimum PSD CI parameters without the need of iterative optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Surrogate modeling of Monte Carlo radiation transport with convolutional neural networks for shielding optimization

Here, we present a machine learning (ML)-based surrogate model using convolutional neural networks (CNN) designed to emulate the attenuation of neutron fields as they pass through various shielding materials. This model can compute the outgoing neutron flux almost instantaneously and achieves reasonable accuracy compared to traditional Monte Carlo (MC)-based codes, which are computationally intensive. This emulator alleviates the complexity of neutron radiation transport through shielding materials by reducing the dimensionality and enables shielding optimization for a known radiation environment. This optimization process, which would have taken an unrealistic timeline due to several complex radiation transport simulations, can now be achieved in minutes, thus increasing computational capabilities in radiation shielding assessment. We demonstrate the applications of this emulator in computing effective dose rates and optimizing shielding solutions for a heavy-ion accelerator facility, such as the Facility for Rare Isotope Beams, where secondary neutrons produced via beam interactions dominate the radiation environment.

accelerator shielding↗

DOE OSTI2017

HPC formulations of optimization algorithms for tensor completion

Tensor completion is a powerful tool used to estimate or recover missing values in multi-way data. It has seen great success in domains such as product recommendation and healthcare. Tensor completion is most often accomplished via low-rank sparse tensor factorization, a computationally expensive non-convex optimization problem which has only recently been studied in the context of parallel computing. In this work, we study three optimization algorithms that have been successfully applied to tensor completion: alternating least squares (ALS), stochastic gradient descent (SGD), and coordinate descent (CCD++). We explore opportunities for parallelism on shared- and distributed-memory systems and address challenges such as memory- and operation-efficiency, load balance, cache locality, and communication. Among our advancements are a communication-efficient CCD++ algorithm, an ALS algorithm rich in level-3 BLAS routines, and an SGD algorithm which combines stratification with asynchronous communication. Furthermore, we show that introducing randomization during ALS and CCD++ can accelerate convergence. We evaluate our parallel formulations on a variety of real datasets on a modern supercomputer and demonstrate speedups through 16384 cores. Further, these improvements reduce time-to-solution from hours to seconds on real-world datasets. We show that after our optimizations, ALS is advantageous on parallel systems of small-to-moderate scale, while both ALS and CCD++ provide the lowest time-to-solution on large-scale distributed systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Numerical analysis and wave tank validation on the optimal design of a two-body wave energy converter

To improve the performance of a ‘point absorber’ type wave energy converter (WEC), an additional submerged body can be deployed. The submerged body can be used to increase the equivalent excitation force on the WEC, as well as provide resonance tuning. This paper presents numerical analysis and experimental validation of a two-body point absorber type WEC using a mechanical motion rectifier (MMR) based power takeoff. The two-body point absorber consists of a floating buoy connected to a neutrally buoyant submerged body via the power-takeoff. The mechanical motion rectifier and a ball screw translate the relative heave motion of the two bodies into unidirectional rotation, which in turn spins a generator. Frequency domain analysis suggests there is an optimal submerged body mass for maximum WEC power absorption. Regular wave simulations in the time domain are compared to the results obtained in the frequency domain. While the time domain and frequency domain results predict the same optimal mass ratio, time domain analysis provides a more complex and accurate power result. To validate the time domain model, experimental wave tank testing is conducted using a 1:30 scale model WEC. The experiment shows the two-body WEC can produce twice the amount of power as the single-body WEC with same floating buoy and can be further increased by PTO design and power electronics optimization. Furthermore, wave tank testing shows the two-body WEC has a capture width ratio up to 58% at 59 kW/m and 51% at 36 kW/m.

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

Control-inspired design and power optimization of an active mechanical motion rectifier based power takeoff for wave energy converters

Ocean waves have high energy density and are persistent and predictable. Yet, converting wave energy to a useable form remains challenging. A significant hurdle is the oscillatory nature of waves resulting in the alternating loads, which necessitate the use of rectification at some stage of the energy conversion. This research effort presents a novel design of active mechanical motion rectifier (AMMR) for the power takeoff (PTO), which provides enhanced controllability and better power performance when compared to passive mechanical motion rectifiers (MMR). Inspired by transistors used in synchronous electrical rectifiers, the proposed design uses controllable electromagnetic clutches in the mechanical transmission to allow active engagement-disengagement control; thus, rectifying the oscillatory motion into a unidirectional rotation for high energy conversion efficiency and allowing the generator in unidirectional rotation to control the bidirectional wave capture structure for maximizing the power output. A semi-analytical computational approach is developed to efficiently evaluate the optimal power achieved using the proposed AMMR-based PTO and active control. It is found that the AMMR-based PTO design yields a higher optimal power than the previous passive MMR design across the wave spectrum. The influences of generator inertia and reactive power are discussed. Furthermore, the effects of control parameters on the power output and the optimal trajectories are analyzed. Wave tank tests with the AMMR prototype demonstrated the effectiveness of AMMR based PTO design and validated the numerical analysis.

16 TIDAL AND WAVE POWER↗

DOE OSTI2023

Sustainable bioleaching of lithium-ion batteries for critical metal recovery: Process optimization through design of experiments and thermodynamic modeling

Recycling spent lithium-ion batteries (LIBs) could alleviate supply risks for critical metals and be less harmful to the environment compared to new production of metals from mining. Developing a cost-effective LIB bioleaching process could be a promising alternative to traditional energy-intensive recycling technologies. Here, this study aimed to optimize bioleaching conditions for maximum economic competitiveness through design of experiments using iterative response surface methodology (RSM), assisted by thermodynamic modeling. The optimal condition was identified as 2.5% pulp density in 75 mM gluconic acid biolixiviant at 55°C for 30 h which could recover 57%–84% of nickel, 71%–86% of cobalt, and 100% of lithium and manganese, yielding a 17%–26% net profit margin. The recommended pulp density and acid concentrations, together with the observed metal solubilization, were supported by thermodynamic modeling predictions. Our study demonstrated that combining RSM with thermodynamic simulations could be a powerful tool for optimizing bioleaching conditions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Distributed optimization and control for autonomous distributed energy resource power dispatch and frequency regulation considering communication failures

Distributed energy resources (DERs) can significantly enhance grid flexibility by supplying power and secondary frequency regulation (SFR) services. Yet, their large number and dispersed nature limit the effectiveness of traditional centralized power dispatch and frequency control schemes, and expose the system to single-point communication failures. This paper presents a unified distributed optimization and control framework for DER power dispatch and SFR provision. A transmission-loss-aware distributed direct current optimal power flow is first formulated to optimize DER power dispatch and reserve scheduling. On top of this, a fully distributed control scheme for DER autonomous SFR provision is developed to allocate automatic generation control signals cost-effectively while ensuring robustness to communication link disruptions. The framework is validated on IEEE 14-bus and 39-bus transmission systems with large-scale distribution feeders using transmission-distribution dynamic co-simulation, demonstrating reliable and autonomous DER power dispatch and SFR provision under diverse operating conditions and communication contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Optimizing energy yield of monolithic perovskite/silicon tandem solar cells in real-world Conditions: The impact of luminescent coupling

Efficient light management is key to maximizing power conversion efficiency (PCE) in monolithic perovskite/silicon tandem solar cells. Achieving peak efficiency requires closely matched current generation in all junctions, especially in integrated configurations. However, real-world conditions vary significantly due to factors such as sunlight spectrum, diffuse-to-direct sunlight ratio, angular distribution of light, subcell temperature coefficients, and ground reflection. This study introduces a comprehensive optical and device simulation to optimize perovskite/silicon tandem cells, considering experimental luminescent coupling (LC) efficiency and its dependence on working conditions, alongside variations in radiative recombination, effect of temperature on absorptivity spectra, and cloud cover. Our results show potential energy yield improvements of up to 1.4 % with LC, based on current perovskite radiative recombination records, and up to 4 % with direct bandgap materials. Although radiative recombination's dependence on excitation intensity reduces output power and requires thicker absorbers, LC compensates for these losses. LC also lowers the optimized bandgap for the perovskite top cell from 1.72 eV to 1.64–1.68 eV, or even lower in regions with redshifted irradiance. Additionally, optimization revealed that thinner silicon bottom cells require a higher perovskite top cell bandgap, impacting the balance between fabrication cost and cell stability.

14 SOLAR ENERGY↗

DOE OSTI2023

A survey of techniques for optimizing transformer inference

Recent years have seen a phenomenal rise in the performance and applications of transformer neural networks. The family of transformer networks, including Bidirectional Encoder Representations from Transformer (BERT), Generative Pretrained Transformer (GPT) and Vision Transformer (ViT), have shown their effectiveness across Natural Language Processing (NLP) and Computer Vision (CV) domains. Transformer-based networks such as ChatGPT have impacted the lives of common men. However, the quest for high predictive performance has led to an exponential increase in transformers' memory and compute footprint. Researchers have proposed techniques to optimize transformer inference at all levels of abstraction. Further, this paper presents a comprehensive survey of techniques for optimizing the inference phase of transformer networks. We survey techniques such as knowledge distillation, pruning, quantization, neural architecture search and lightweight network design at the algorithmic level. We further review hardware-level optimization techniques and the design of novel hardware accelerators for transformers. We summarize the quantitative results on the number of parameters/FLOPs and the accuracy of several models/techniques to showcase the tradeoff exercised by them. We also outline future directions in this rapidly evolving field of research. We believe that this survey will educate both novice and seasoned researchers and also spark a plethora of research efforts in this field.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Optimal assignment for the single-household shared autonomous vehicle problem

Autonomous vehicles have the potential to transform the way people are transported. While driverless technology may mean fewer vehicles are required to transport people to and from their daily activities, such changes may result in increased congestion or total miles traveled. In this study, we solve the single-household shared autonomous vehicle problem to identify cost-optimal routings of vehicles throughout the day. Such a tool will be useful for consumers seeking to minimize cost and for regulators seeking to understand and predict how people may behave in different scenarios. Here, we provide a thorough literature review and construct a mixed-integer linear program to minimize the daily travel cost of a household attending a given set of activities. Since solution time is a determinant for applicability of such a model, we present the model in a component-wise fashion. This approach allows us to understand which features most affect the problem complexity and solution time. We note that modeling carpooling is the feature that most increases time to find an optimal solution, and we therefore propose a novel modeling technique for carpooling two people. We illustrate the performance of our model by comparing it with other models from the literature and note that our model can solve significantly larger problem instances and in a time that is short enough to facilitate real-time scheduling. We also highlight the utility of our model for regulators, who can use it to analyze quickly produced optimal routes under different cost/tax scenarios.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Enhancement of disposal efficiency for deep geological repositories based on three design factors - Decay heat optimization, increased thermal limit of the buffer and double-layer concept

This study investigates the enhancement of disposal efficiency for deep geological repositories (DGRs) based on three design factors: decay heat optimization, increased thermal limit of the buffer, and double-layer concept using coupled thermo-hydro-mechanical (THM) numerical simulations. Decay heat optimization is achieved by iteratively emplacing spent nuclear fuels having the maximum and minimum decay heat in a canister. Disposal areas can be reduced by 20 % to 40 % compared to the current reference disposal system in Korea (KRS+) in accordance with the combinations of the three design factors, alleviating challenges in site selection for the DGR. This study additionally identifies an optimal layer spacing of 500 m for the double-layer concept in the viewpoint of the buffer temperature, where thermal interaction between the upper and lower layers nearly disappears. However, determining the ultimate disposal and layer spacing requires engineering judgement, considering not only the thermal performance of the DGR but also various factors such as cost and difficulties of the construction and rock mass stability. DGRs designed with an increased thermal limit of the buffer poses a greater probability of rock mass failure around disposal tunnels and deposition holes due to elevated thermal stresses. Densely arranged heat sources for the DGRs with enhanced disposal efficiency lead to larger temperature increase even at the far-field scale, raising a possibility of thermally driven fracture shear activation with associated hydraulic, mechanical, and seismic changes.

58 GEOSCIENCES↗

DOE OSTI2022

Mapping the space of quasisymmetric stellarators using optimized near-axis expansion

A method is demonstrated to rapidly calculate the shapes and properties of quasi-axisymmetric and quasi-helically symmetric stellarators. In this approach, optimization is applied to the equations of magnetohydrodynamic equilibrium and quasisymmetry, expanded in the small distance from the magnetic axis, as formulated by Garren & Boozer [ Phys. Fluids B, vol. 3, 1991, p. 2805]. Due to the reduction of the equations by the expansion, the computational cost is significantly reduced, to times of the order of 1 cpu second, enabling wide and high-resolution scans over parameter space. In contrast to traditional stellarator optimization, here, the cost function serves to maximize the volume in which the expansion is accurate. A key term in the cost function is $\| \boldsymbol {\nabla }\boldsymbol B \|$ , the norm of the magnetic field gradient, to maximize scale lengths in the field. Using this method, a database of $5\times 10^5$ optimized configurations is calculated and presented. Quasisymmetric configurations are observed to exist in continuous bands, varying in the ratio of the magnetic axis length to average major radius. Several qualitatively new types of configuration are found, including quasi-helically symmetric fields in which the number of field periods is two or more than six.

Landreman, Matt (ORCID:000000027233577X)↗

DOE OSTI2023

Initial Characterization and Optimization of the Liquid Sampling-Atmospheric Pressure Glow Discharge Ionization Source Coupled to an Orbitrap Mass Spectrometer for the Determination of Plutonium

Plutonium measurements are essential to the nuclear forensics and safeguards community. The liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled with an Orbitrap mass spectrometer is a proven platform for uranium isotope ratio determinations. Here, this work expands the LS-APGD-Orbitrap platform capabilities by reporting the first-ever analysis of plutonium with the LS-APGD and the first-ever measurement of elemental plutonium with an Orbitrap mass spectrometer. This coupling has the potential to dramatically reduce the complex sample manipulations required for traditional analysis techniques employed for actinide isotope ratio determinations. As a first step toward the goal of simultaneous uranium and plutonium isotope ratio determinations, the initial characterization and optimization of the platform for the detection of plutonium are reported. Collision-induced dissociation modality settings were optimized to reduce water-related and other molecular clusters containing plutonium, maximizing 242 Pu 16 O 2 + responses. A design of experiments study was conducted to optimize the discharge conditions of the dual-electrode LS-APGD toward the responsivity of 242 Pu 16 O 2 +. The measurement sensitivity was determined from a Pu response curve, yielding a limit of detection of 10 fg (absolute) of total analyte when data was collected and processed with a Spectroswiss FTMS Booster X2 data acquisition system. Additionally, plutonium and uranium were measured in a simultaneous acquisition, and each analyte remained unaffected by the other. It is believed that the LS-APGD-Orbitrap platform could be a valuable addition to the nuclear forensics’ toolbox and, indeed, other scientific disciplines and regulatory communities in which rapid, high-resolution plutonium determinations are paramount.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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 OSTI2020

NWPEsSe: an Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

Global optimization constitutes an important and fundamental problem in theoretical studies in many chemical fields, such as catalysis, materials or separations problems. In this paper, a novel algorithm has been developed for the global optimization of large systems including neat and ligated clusters in gas phase, and supported clusters in periodic boundary conditions. The method is based on an updated artificial bee colony (ABC) algorithm method, that allows for adaptive-learning during the search process. The new algorithm is tested against four classes of systems of diverse chemical nature: gas phase Au_55, ligated Au_8^(2+), Au_8 supported on graphene oxide and defected rutile, and a large cluster assembly ?[Co?_6 Te_8 (PEt_3 )_6][C_60 ]_n, with sizes ranging between 1 to 3 nm and containing up to 1300 atoms. Reliable global minima (GMs) are obtained for all cases, either confirming published data or reporting new lower energy structures. The algorithm and interface to other codes in the form of an independent program, Northwest Potential Energy Search Engine (NWPEsSe), is freely available and it provides a powerful and efficient approach for global optimization of nanosized cluster systems. The work described in this publication was performed at Pacific Northwest National Laboratory (PNNL), which is operated by Battelle for the United States Department of Energy (DOE) under Contract DE-AC05-76RL0180. J. Z. and V.-A. G. acknowledge support from DOE, Office of Science, Office of Basic Energy Sci-ences, Chemical, Geological and Biological Sciences Division and computing resources from PNNL’s Research Computing Facility and the National Energy Research Scientific Computing Center.

Zhang, Jun↗

DOE OSTI2022

The Evolution of LiNi 0.5 Mn 0.3 Co 0.2 O 2 Particle Damage from Fast Charging in Optimized, Full Li-Ion Cells

Fast charging batteries are critical to the widespread adoption of electric vehicles to compete with refueling times of combustion-based vehicles. In the near term, adapting current commercial battery technologies to perform better under fast charging conditions through engineering optimizations will greatly expedite the process while exploratory fast-charging electrode materials are being pursued. To do so, the degradation modes in optimized Li-ion batteries need to be completely explored to understand fast charging limits while maintaining a high energy density and a long cycle life. While lithium plating on graphite still remains a challenge, cathode degradation also plays a key role in battery performance. In this work, we used nano- and micro-X-ray computed tomography to characterize the mechanical degradation of LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) in optimized Li-ion batteries cycled at three rates, 1C, 6C, and 9C, and at different stages of cycle life, 225 and 600 cycles. We report despite using a conservative upper voltage cutoff limit aimed to minimize extensive cathode degradation, higher charging rates and increased cycling caused the polycrystalline NMC532 particles to fracture and pulverize, which likely drives cathode capacity fade and contributes to the decrease in overall cell performance.

25 ENERGY STORAGE↗