Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “global 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.

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

At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimal Twirling Depth for Classical Shadows in the Presence of Noise

The classical shadows protocol is an efficient strategy for estimating properties of an unknown state p using a small number of state copies and measurements. In its original form, it involves twirling the state with unitaries from some ensemble and measuring the twirled state in a fixed basis. It was recently shown that for computing local properties, optimal sample complexity (copies of the state required) is remarkably achieved for unitaries drawn from shallow depth circuits composed of local entangling gates, as opposed to purely local (zero depth) or global twirling (infinite depth) ensembles. Here, we consider the sample complexity as a function of the depth of the circuit, in the presence of noise. We find that this noise has important implications for determining the optimal twirling ensemble. Under fairly general conditions, we (i) show that any single-site noise can be accounted for using a depolarizing noise channel with an appropriate damping parameter f, (ii) compute thresholds f th at which optimal twirling reduces to local twirling for Pauli operators, (iii) nth order Renyi entropies (n ≥2), and (iv) provide a meaningful upper bound t max on the optimal circuit depth for any finite noise strength f, which applies to observables and entanglement entropy measurements. In conclusion, these thresholds strongly constrain the search for optimal strategies to implement shadow tomography and are easily tailored to the experimental system at hand.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

From neutron star observables to the equation of state. I. An optimal parametrization

The increasing number and precision of measurements of neutron star masses, radii, and, in the near future, moments of inertia offer the possibility of precisely determining the neutron star equation of state (EOS). One way to facilitate the mapping of observables to the EOS is through a parametrization of the latter. We present here a generic method for optimizing the parametrization of any physically allowed EOS. We use mock EOS that incorporate physically diverse and extreme behavior to test how well our parametrization reproduces the global properties of the stars, by minimizing the errors in the observables of mass, radius, and the moment of inertia. We find that using piecewise polytropes and sampling the EOS with five fiducial densities between ∼1–8 times the nuclear saturation density results in optimal errors for the smallest number of parameters. Specifically, it recreates the radii of the assumed EOS to within less than 0.5 km for the extreme mock EOS and to within less than 0.12 km for 95% of a sample of 42 proposed, physically motivated EOS. Such a parametrization is also able to reproduce the maximum mass to within 0.04 M{sub ⊙} and the moment of inertia of a 1.338 M{sub ⊙} neutron star to within less than 10% for 95% of the proposed sample of EOS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Editorial: Multi-Omics Technologies for Optimizing Synthetic Biomanufacturing

Industrial manufacturing endures as an essential human activity yielding a variety of useful products; it plays a significant role in the global economy with huge impacts in everyday life. However, the manufacturing process requires consumption of various raw materials (especially petroleum derivatives), generates a variety of harmful waste products, causes pollution, and is energetically inefficient. Biological manufacturing from sustainable, affordable, and scalable feedstocks potentially enables the displacement of the entire portfolio of currently available products produced by industrial processes, enabling the manufacturing of renewable and eco-friendly products (Clomburg et al., 2017). Thus, successful development of a robust biomanufacturing strategy and technology platform, based on the latest advances in synthetic biology and chemical catalysis, will decrease both the cost and production time compared with previous manufacturing processes. Development of biomanufacturing processes using a synthetic biology platform requires the multidisciplinary efforts of science and engineering fields including molecular biology, microbiology, genetic engineering, informatics, metabolic modeling and chemical or process engineering (El Karoui et al., 2019).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Scale-Bridging Optimization Framework for Desalination Integrated Produced Water Networks

In this work, we develop a Pyomo-based non-linear optimization strategy that includes rigorous MVR models. The detailed desalination unit is integrated into the multiperiod produced water network problem using the trust region filter (TRF) method. TRF decomposes the integrated problem into a master problem consisting of the network variables and a simplified surrogate model for the detailed desalination unit. The surrogate is updated using zero and first-order corrections from the optimal solution of the detailed models at every iteration. This framework allows us to co-optimize the design of the desalination units and operating policy for the multiperiod network. A common design is ensured across all periods using global capacity constraints. We validate the solution obtained using the TRF method by solving the full integrated problem for small network instances and show our results on real case studies on produced water networks from the Permian and Appalachian basins. In this work, we describe our TRF formulation, give details on our implementation in Pyomo, and analyze the results obtained by solving the optimization problem using IPOPT. We also present a discussion on the computational efficiency and scaling using the TRF approach against a full-scale integration of the rigorous models within the water network.

Naik, Sakshi↗
DOE OSTI2020

Data Assimilative Optimization of WSA Source Surface and Interface Radii using Particle Filtering

TheWang-Sheeley-Arge (WSA) model estimates solar wind speed and interplanetary magnetic field polarity in the inner heliosphere using global photospheric magnetic field maps. WSA employs the Potential Field Source Surface (PFSS) and Schatten Current Sheet (SCS) models to determine the Sun's global coronal magnetic field. The PFSS and SCS models are connected through two radial parameters, the source surface and interface radii, which specify the overlap region between the inner SCS and outer PFSS models. Though both radii values are adjustable, they have typically been fixed to 2.5 solar radii. Our work highlights how solar wind predictions improve when the radii are allowed to vary over time. Data assimilation using particle filtering (sequential Monte Carlo) is used to infer optimal values over a fixed time window. Solar wind model predictions and satellite observations are compared with a newly developed quality-of-agreement prediction metric. The agreement metric between the model and observations is assumed to correspond to the probability of the two key WSA model parameters, the source surface and interface radii, where the highest metric value implies the optimal radii.We find that the optimal particle filter values of solar radii can perform twice as well as standard values for an exploratory period during Carrington Rotation 1901, with these values also reducing nonphysical kinking effects seen in solar magnetic field lines. Data assimilation choices of input realization and time frame have implications for variation in the solar wind over time. We present this work's theoretical context and practical applications for prediction accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Monte Carlo simulations for water adsorption in porous materials: Best practices and new insights

Technologies based on water adsorption such as water harvesting from air have tremendous potential in mitigating important global crises such as water scarcity. An important challenge to the deployment of such technologies is finding optimal adsorbent materials. Given the large materials space of available adsorbents, large-scale computational screening can be extremely helpful for this task. This work explores the methods and details associated with such screening procedures and recommends best practices. We also shed light on the limitations of traditionally used and inexpensive to compute prescreening approaches involving geometric and energetic features to predict water adsorption behavior of porous materials. Such approaches can provide general trends to predict adsorption behavior but may lead to the overlook of potentially important structures due to the complex nature of water adsorption. Finally, this study offers insights for future water adsorption simulations to facilitate the development of optimal water adsorbents.

42 ENGINEERING↗
DOE OSTI2019

Scalable Representation Learning for Long-Term Augmented Reality-Based Information Delivery in Collaborative Human-Robot Perception

Augmented reality (AR)-based information delivery has been attracting an increasing attention in the past few years to improve com- munication in human-robot teaming. In the long-term use of AR systems for collaborative human-robot perception, one of the biggest challenges is to perform place and scene matching under long-term environmental changes, such as dramatic variations in lighting, weather and vegetation across di erent times of the day, months, and seasons. To address this challenge, we introduce a novel representation learning approach that learns a scalable long-term representation model that can be used for place and scene matching in various long-term conditions. Our approach is formulated as a regularized optimization problem, which selects the most representative scene templates in di erent scenarios to construct a scalable representation of the same place that can exhibit signi cant long-term environment changes. Our approach adaptively learns to select a small subset of the templates to construct the representation model, based on a user-de ned representativeness threshold, which makes the learned model highly scalable to the long-term variations in real-world applications. To solve the formulated optimization problem, a new algo- rithmic solver is designed, which is theoretically guaranteed to converge to the global optima. Experiments are conducted using two large-scale benchmark datasets, which have demonstrated the superior performance of our approach for long-term place and scene matching.

42 ENGINEERING↗
DOE OSTI2016

Resource Sharing Controls Gene Expression Bursting

Episodic gene expression, with periods of high expression separated by periods of no expression, is a pervasive biological phenomenon. This bursty pattern of expression draws from a finite reservoir of expression machinery in a highly time variant way, i.e., requiring no resources most of the time but drawing heavily on them during short intense bursts, that intimately links expression bursting and resource sharing. Yet, most recent investigations have focused on specific molecular mechanisms intrinsic to the bursty behavior of individual genes, while little is known about the interplay between resource sharing and global expression bursting behavior. In this paper, we confine Escherichia coli cell extract in both cell-sized microfluidic chambers and lipid-based vesicles to explore how resource sharing influences expression bursting. Interestingly, expression burst size, but not burst frequency, is highly sensitive to the size of the shared transcription and translation resource pools. The intriguing implication of these results is that expression bursts are more readily amplified than initiated, suggesting that burst formation occurs through positive feedback or cooperativity. When extrapolated to prokaryotic cells, these results suggest that large translational bursts may be correlated with large transcriptional bursts. This correlation is supported by recently reported transcription and translation bursting studies in E. coli. Finally, the results reported here demonstrate a strong intimate link between global expression burst patterns and resource sharing, and they suggest that bursting plays an important role in optimizing the use of limited, shared expression resources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Curl-free magnetic fields for stellarator optimization

This paper describes a new and efficient method of defining an annular region of a curl-free magnetic field with specific physics and coil properties that can be used in stellarator design. Three statements define the importance: (1) Codes can follow an optimized curl-free initial state to a final full-pressure equilibrium. The large size of the optimization space of stellarators, approximately 50 externally produced distributions of magnetic field, makes success in finding a global optimum largely determined by the starting point. (2) The design of a stellarator is actually improved when the central region of the plasma has rapid transport with the confinement provided by a surrounding annulus of magnetic surfaces with low transport. (3) The stellarator is unique among all fusion concepts, inertial as well as magnetic, in not using the plasma itself to provide an essential part of its confinement concept. This permits reliable computational design, which opens a path to faster, cheaper, and more certain achievement of fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Analysis of Alfven eigenmodes destabilization by energetic particles in TJ-II using a Landau-closure model

Alfvén Eigenmodes (AE) can be destabilized by energetic particles in neutral beam injection (NBI) heated plasmas through inverse Landau damping and couplings with gap modes in the shear Alfvén continua. In this paper, we describe the linear evolution of the poloidal flux and the toroidal component of the vorticity in a full 3D system using the reduced MHD equations, density and parallel velocity moments for the energetic particles as well as the geodesic acoustic wave dynamics. A closure relation adds the Landau damping and resonant destabilization effects in the model. We apply the model to study the Alfvén modes stability in TJ-II, performing a parametric analysis in a range of realistic values of energetic particle β ($\beta_{f}$ ), ratios of thermal/Alfvén velocities ($V_{\rm th}/V_{\rm A0}$ ), energetic particle density profiles and toroidal modes (n) including toroidal and helical couplings. The study predicts a large helical coupling between different toroidal modes and the destabilization of helical Alfvén eigenmodes (HAE) with frequencies similar to the AE activity measured in TJ-II, between 50–400 kHz. The analysis has also revealed the destabilization of GAE (global Alfvén eigenmodes), TAE (toroidal Alfvén eigenmodes) and EPM (energetic particle modes). For the modes considered here, optimized TJ-II operations require a $\rlap{-} \iota$ profile in the range of $[0.845, 0.979]$ to stabilize AEs in the inner and middle plasma. AEs in the plasma periphery cannot be fully stabilized, although for a configuration with $\rlap{-} \iota = [0.945, 1.079]$ , only $n=7, 11, 15$ AE are unstable with a growth rate 4 times smaller compared to the standard $\rlap{-} \iota = [1.54, 1.68]$ case and a frequency of 100 kHz. Finally, we reproduce the frequency sweeping evolution of the AE frequency observed in TJ-II as the $\rlap{-} \iota$ profile is varied. The AE frequency sweeping is caused by consecutive changes of the instability dominant modes between different helical families.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

A Global Analysis of Light and Charge Yields in Liquid Xenon

Here, we present an updated model of light and charge yields from nuclear recoils in liquid xenon with a simultaneously constrained parameter set. A global analysis is performed using measurements of electron and photon yields compiled from all available historical data, as well as measurements of the ratio of the two. These data sweep over energies from keV and external applied electric fields from V/cm. The model is constrained by constructing global cost functions and using a simulated annealing algorithm and a Markov Chain Monte Carlo approach to optimize and find confidence intervals on all free parameters in the model. This analysis contrasts with previous work in that we do not unnecessarily exclude datasets nor impose artificially conservative assumptions, do not use spline functions, and reduce the number of parameters used in NEST v 0.98. Here, we report our results and the calculated best-fit charge and light yields. These quantities are crucial to understanding the response of liquid xenon detectors in the energy regime important for rare event searches such as the direct detection of dark matter particles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Toward a least-effort principle for evaluating prices of elements as indicators of sustainability

In this article, we explore simplifying mechanisms in materials economics for conceptionally organizing the flows of chemical elements into society. We use the concept of rank, which plays a crucial role in information theory where power laws are involved, and is a useful measure for seeking extremal principles. Borrowing from an analogy to Zipf’s law leads to a power-law relationship between abundance and rank that—pressing the Zipf’s law analogy further—may suggest that the price paid for elemental materials optimizes efficient utilization. Factors such as weight, volume, and moles in the earth's crust or in global mining production of elements are used in our analysis. For this research, 42 elements with price and production data for the year 2010 (a relatively typical year) were considered. We observe that the role of the volume from global mining production dominates in materials economics and indicate that elements such as Te and He should be sold at prices at leas ~ 100–1000 times more than their present price for efficient utilization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Evaluation of Portable X-Ray Fluorescence (XRF) Analyzer for Zirconium-Thickness Measurements

This Technical Evaluation Report provides details of preliminary testing/experiments performed using a handheld X-ray fluorescence analyzer. The analyzer will be utilized in upcoming fuel-foil-rolling optimization studies at the INL. The studies are being performed in support of DOE’s Office of Global Threat Reduction -- Reactor Conversion Subprogram. Details of the equipment used, operating parameters, and measurement results are provided in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Correcting the PFNS for more consistent fission modeling

For FY20, we had a deliverable to write a report detailing efforts to simultaneously evaluate both the prompt neutron multiplicity, $\overline{ν}$, and the prompt neutron fission neutron spectrum, PFNS, using CGMF. CGMF is the LANL-developed fission fragment decay code that consistently evaporates prompt neutrons and γ rays using the Hauser-Feshbach statistical theory of compound reactions. The decay begins by constructing the initial conditions of the fission fragments, then decaying each one from the excited state by neutrons and γ rays, conserving energy, momentum, spin, and parity in each step of the emission. The initial conditions of the fragments, along with the multiplicity, energy, and direction of each emitted neutron or γ ray, are recorded, allowing for the full reconstruction of the fission event. These event histories allow us to reconstruct average quantities, as well as correlations between observables, that can be compared with experimental or evaluated data. In that initial report, although there was already a favorable comparison between $\overline{ν}$ from CGMF, experiment, and the current ENDF/B-VIII.0 evaluation, we showed that there was still significant work to be done to improve the PFNS from CGMF. Historically, the PFNS is calculated too soft by Hauser-Feshbach fission models, and CGMF is no exception. The incorrect shape presents a significant challenge in fission modeling, including for our understanding of the fission process and for our ability to consistently calculate and predict a variety of prompt fission observables (such as fission fragment initial conditions, neutron and γ-ray multiplicities and energies, and the correlations between all observables). In our companion report, we detail our success in using CGMF to evaluate $\overline{ν}$. Although not included in the optimization explicitly, we also keep the initial conditions of the fission fragments physical, along with reproducing reasonably well the neutron multiplicity distribution. As we would expect from the sensitivities calculations from, the average neutron energies change very little from the $\overline{ν}$ optimization along with the PFNS (as will be shown in Sec. 2.6). The conclusion was that the global and statistical models would have to be investigated instead of just the fission fragment initial conditions (as is sufficient for $\overline{ν}$). This report details those efforts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Performance Results on CPU/GPU Exascale Architectures for OMEGA: The Ocean Model for E3SM Global Applications

The US Department of Energy (DOE) conducts climate simulations on some of the world’s largest supercomputers. These exascale machines use heterogeneous architectures with both CPUs and GPUs, and scientific codes must adapt to make full use of this computing power. Los Alamos National Lab is developing Omega: The Ocean Model for E3SM Global Applications, which is specifically designed for modern exascale computers. It uses external libraries that have been optimized for a variety of architectures to run on different supercomputers. Omega is an unstructured-mesh ocean model based on TRiSK numerical methods. It will be the new ocean component of the DOE’s Energy Exascale Earth System Model (E3SM). The algorithms in Omega follow those of the current ocean component, MPAS-Ocean, but it will be written in C++ rather than Fortran to take advantage of the Kokkos performance portability library. Omega spatial operators are written as Kokkos kernels to run efficiently on both CPUs and GPUs. Work on Omega began in 2023 with a new C++ framework for unstructured mesh partitioning, halo exchanges, parallel IO, and Kokkos interfaces. The current version, Omega-0, is being developed to solve the shallow water equations and at present includes all of the tendency terms but not time stepping. Here we share the results of Omega-0 verification and performance testing. Verification includes unit tests implemented with CTest as well as convergence tests in Polaris, an in-house python package with a large suite of test problems. Performance tests compare simulations conducted on CPUs versus GPUs and across different architectures: tests are run on Frontier, which has AMD “Optimized 3rd Gen EPYC” CPUs and AMD MI250X GPUs, as well as Perlmutter, which is composed of AMD EPYC 7763 CPUs and NVIDIA A100 GPUs.

58 GEOSCIENCES↗
DOE OSTI2023

Perspectives on biorefineries in microbial production of fuels and chemicals

Microbes drive our complex biosphere by regulating the global ecosystem through cycling elements and energy. Humankind has barely begun leveraging this biotransformation capacity to impact global economies and ecologies. Advances in genetic engineering, molecular analysis, metabolic flux modeling, microbial consortia/biome mapping and engineering, cell-free bioproduction, artificial intelligence/machine learning and the ever expanding -omics frontiers have set the stage for paradigm changes to how humankind produces, uses, transforms, and recycles carbon and energy through microbes. Harnessing this enormous potential could drive a global bioeconomy and manage carbon at a planetary level but requires understanding and application at a grand scale across a broad range of science and engineering disciplines. The penultimate manifestation of these advances is the “bio-refinery”, which is often referenced, but is a long way from being fully developed as a global carbon management platform. Broadening the feed stocks, processing operations, and product portfolio to a sequential cascade optimizing the conversion as a whole instead of limited outputs could greatly advance deployment and stability of a bioeconomy.

09 BIOMASS FUELS↗
NASA NTRS1978

The modification and application of Kuo's parameterization of cumulus convection in middle latitudes

An evaluation to reveal physical insight into the involved mechanisms through a combination of the large scale heat and moisture budgets and formulation of the latent heat released was performed. To improve upon the treatment of the interaction of deep convection with the environment, modifications consisting of considerations of the large scale moisture supply and of the vertical transport of moisture and of dry static energy inside the cloud are made. Also, a two layer cloud ensemble model is combined with the modified scheme. An examination of the modified scheme is performed by combining the large scale heat and moisture budgets and the modified formulation of the latent heat released. The modified parameterization procedures are compared with the original scheme, and the results of tests of both schemes are discussed. A variational optimization scheme is developed to analyze the wind field such that the integrated continuity equation and the global boundary condition are satisfied.

Liang, W. J.↗
NASA NTRS1978

Global analysis of a buck regulator

Sufficient conditions for global stability of a buck regulator using a discrete control law are found. The method of paired systems and Liapunov functions are used to establish global stability and to study the convergence of the regulator. A heuristic argument is given that the optimal switching curves associated with the paired continuous systems approximate the optimal switching curves of the discrete systems.

Edwards, D. B.↗