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At least 181 records · Page 10

Optimal error analysis of spectral methods with emphasis on non-constant coefficients and deformed geometries

The numerical analysis of spectral methods when non-constant coefficients appear in the equation, either due to the original statement of the equations or to take into account the deformed geometry, is presented. Particular attention is devoted to the optimality of the discretization even for low values of the discretization parameter. The effect of some overintegration is also addressed, in order to possibly improve the accuracy of the discretization.

Maday, Yvon↗

Piezoelectric impedance-based high-accuracy damage identification using sparsity conscious multi-objective optimization inverse analysis

Two elements are essential in structural health monitoring utilizing dynamic responses: response measurement with high-frequency contents, i.e., small characteristic wavelengths, that can adequately reflect damage features, and effective inverse identification analysis that is however oftentimes under-determined. The advancement of smart structure integration has led to active interrogation through frequency-sweeping piezoelectric impedance measurement at high frequency range. In this research we develop a multi-objective optimization formulation for the identification of damage location and severity utilizing piezoelectric impedance. While one optimization objective is to match the response measurement with finite element model prediction in the damage parametric space, the other is the number of locations of damage, i.e., the sparsity of damage index as the solution vector, since damage usually occurs within a small number of locations. This multi-objective formulation fits well the under-determined nature of damage identification, as it naturally provides multiple solutions as basis for further elucidation. The challenge remaining is how to find a small solution set that can include the actual damage scenario. Here we develop a novel inverse identification framework utilizing the intelligent swarm optimizer which possesses flexibility for enhancement. We first embed a sparsity enforcement process into the population generation of the optimizer, which yields a solution repository intrinsically possessing sparsity. We then apply reinforcement learning so the agents can adaptively opt for local strategies with the aim of enriching the searching patterns to diversify the solutions. Through the incorporation of a Q-table, searching toward more promising directions will be rewarded. Our case analyses employing experimental data indicate that this sparsity-conscious multi-objective particle swarm optimization technique can lead to a small solution set which generally encompasses the true damage scenario. This effectively solves the structural damage identification problem with piezoelectric impedance measurement.

Yang Zhang↗

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

Secondary metabolites are not essential for the growth of microorganisms, but they play a critical role in how microbes interact with their surroundings. In addition to this important ecological role, secondary metabolites also have a variety of agricultural, medicinal, and industrial uses, and thus the examination of secondary metabolism of plants and microbes is a growing scientific field. While the chemical production of certain secondary metabolites is possible, industrial-scale microbial production is a green and economically attractive alternative. This is even more true, given the advances in bioengineering that allow us to alter the workings of microbes in order to increase their production of compounds of interest. This type of engineering requires detailed knowledge of the “chassis” organism’s metabolism. Since the resources and the catalytic capacity of enzymes in microbes is finite, it is important to examine the tradeoffs between various bioprocesses in an engineered system and alter its working in a manner that minimally perturbs the robustness of the system while allowing for the maximum production of a product of interest. The in silico multi-objective analysis of metabolism using genome-scale models is an ideal method for such examinations.

59 BASIC BIOLOGICAL SCIENCES↗

Noise and error analysis and optimization in particle-based kinetic plasma simulations

In this paper we analyze the noise in macro-particle methods used in plasma physics and fluid dynamics, leading to approaches for minimizing the total error, focusing on electrostatic models in one dimension. We begin by describing kernel density estimation for continuous values of the spatial variable x, expressing the kernel in a form in which its shape and width are represented separately. The covariance matrix of the noise in the density is computed, first for uniform true density. The bandwidth of the covariance matrix C(x,y) is related to the width of the kernel. A feature that stands out is the presence of constant negative terms in the elements of the covariance matrix both on and off-diagonal. These negative correlations are related to the fact that the total number of particles is fixed at each time step; they also lead to the property ∫C(x,y)dy = 0. We investigate the effect of these negative correlations on the electric field computed by Gauss's law, finding that the noise in the electric field is related to a process called the Ornstein-Uhlenbeck bridge, leading to a covariance matrix of the electric field with variance significantly reduced relative to that of a Brownian process. For non-constant density, p(x), still with continuous x, we analyze the total error in the density estimation and discuss it in terms of bias-variance optimization (BVO). For some characteristic length l, determined by the density and its second derivative, and kernel width h, having too few particles within h leads to too much variance; for h that is large relative to l, there is too much smoothing of the density. The optimum between these two limits is found by BVO. For kernels of the same width, it is shown that this optimum (minimum) is weakly sensitive to the kernel shape. Next, we repeat the analysis for x discretized on a grid. In this case the charge deposition rule is determined by a particle shape. An important property to be respected in the discrete system is the exact preservation of total charge on the grid; this property is necessary to ensure that the electric field is equal at both ends, consistent with periodic boundary conditions. We find that if the particle shapes satisfy a partition of unity property, the particle charge deposited on the grid is conserved exactly. Further, if the particle shape is expressed as the convolution of a kernel with another kernel that satisfies the partition of unity, then the particle shape obeys the partition of unity. This property holds for kernels of arbitrary width, including widths that are not integer multiples of the grid spacing. Furthermore, we show results relaxing the approximations used to do BVO optimization analytically, by doing numerical computations of the total error as a function of the kernel width, on a grid in x. The comparison between numerical and analytical results shows good agreement over a range of particle shapes. We discuss the practical implications of our results, including the criteria for design and implementation of computationally efficient particle shapes that take advantage of the developed theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The evaluation of several agility metrics for fighter aircraft using optimal trajectory analysis

Several functional agility metrics, including the combat cycle time metric, dynamic speed turn plots, and relative energy state metric, are used to compare turning performance for generic F-18, X-29, and X-31-type aircraft models. These three-degree-of-freedom models have characteristics similar to the real aircraft. The performance comparisons are made using data from optimal test trajectories to reduce sensitivities to different pilot input techniques and to reduce the effects of control system limiters. The turn performance for all three aircraft is calculated for simulated minimum time 180 deg heading captures from simulation data. Comparisons of the three aircraft give more insight into turn performance than would be available from traditional measures of performance. Using the optimal test technique yields significant performance improvements as measured by the metrics. These performance improvements were found without significant increases in turn radius.

Ryan, George W., III↗

Supersonic second order analysis and optimization program user's manual

Approximate nonlinear inviscid theoretical techniques for predicting aerodynamic characteristics and surface pressures for relatively slender vehicles at supersonic and moderate hypersonic speeds were developed. Emphasis was placed on approaches that would be responsive to conceptual configuration design level of effort. Second order small disturbance theory was utilized to meet this objective. Numerical codes were developed for analysis and design of relatively general three dimensional geometries. Results from the computations indicate good agreement with experimental results for a variety of wing, body, and wing-body shapes. Case computational time of one minute on a CDC 176 are typical for practical aircraft arrangement.

Clever, W. C.↗

Improving cosmological analyses of HI clustering by reducing stochastic noise

High-number-density tracers of large-scale structure, such as the HI-rich galaxies measured by 21 cm intensity mapping, have low sampling noise, making them particularly promising as cosmological probes. At large scales, this sampling noise can be subdominant to other scale-independent contributions to the power spectrum; such contributions arise from nonlinear bias, and exceed the sampling noise if at least one of the associated bias coefficients is sufficiently large. This has important consequences for cosmological constraints obtained from such tracers, since it indicates that using the power spectrum does not lead to optimal constraints even in the linear regime. In this paper, we provide a conservative estimate of the possible improvement in constraining power of a 21 cm survey if one were to use an optimal analysis strategy (such as field-level analysis), where only the true sampling noise enters the error budget. We find that improvements in uncertainties on some cosmological parameters can be as large as 50%, depending on redshift, foreground cleaning efficiency, scales used in the analysis, and instrumental noise. One byproduct of our work is measurements of bias parameters and stochasticity for neutral hydrogen in the IllustrisTNG simulation over a wide range of redshifts; we provide simple fitting formulas for these measurements. Furthermore, our results motivate further exploration of new optimal analysis techniques and provide important insights into the constraining power of current and future 21 cm surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantitative Proteomic Analysis of Optimal Cutting Temperature (OCT) Embedded Core-Needle Biopsy of Lung Cancer

With recent advances in understanding the genomic underpinnings and oncogenic drivers of pathogenesis in different subtypes, it is increasingly clear that proper pretreatment diagnostics are essential for the choice of appropriate treatment options for non-small cell lung cancer (NSCLC). Tumor tissue preservation in optimal cutting temperature (OCT) compound is commonly used in the surgical suite. However, proteins recovered from OCT-embedded specimens pose a challenge for LC-MS/MS experiments, due to the large amounts of polymers present in OCT. Here we present a simple workflow for whole proteome analysis of OCT-embedded NSCLC tissue samples, which involves a simple trichloroacetic acid precipitation step. Comparisons of protein recovery between frozen versus OCT-embedded tissue showed excellent consistency with more than 9200 proteins identified. Using an isobaric labeling strategy, we quantified more than 5400 proteins in tumor versus normal OCT-embedded core needle biopsy samples. Gene ontology analysis indicated that a number of proliferative as well as squamous cell carcinoma (SqCC) marker proteins were overexpressed in the tumor, consistent with the patient’s pathology based diagnosis of “poorly differentiated SqCC”. Among the most downregulated proteins in the tumor sample, we noted a number of proteins with potential immunomodulatory functions. Finally, interrogation of the aberrantly expressed proteins using a candidate approach and cross-referencing with publicly available databases led to the identification of potential druggable targets in DNA replication and DNA damage repair pathways. We conclude that our approach allows LC-MS/MS proteomic analyses on OCT-embedded lung cancer specimens, opening the way to bring powerful proteomics into the clinic. .

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Analysis and Optimization of Truncated Scarf Nozzles Subject to External Flow Conditions

Results of a calculation of an optimized truncated scarfed nozzle were compared. The truncated scarfed nozzle was designed for an exit Mach number of 6.0, i.e., the Mach number at the last nozzle characteristic is 6.0, with an external flow Mach number of 5.0. The nozzle was designed by the Rao method for optimum thrust nozzles modified for 2-D flow and truncated scarfed nozzle applications. This design was analyzed using a shock-fitting method for 2-D supersonic flows. Excellent agreement was achieved between the design and analysis. Truncation of the lower nozzle wall (cowl) revealed that there is an optimum length for truncating the cowl without degrading the nozzle performance. Truncation of the nozzle cowl past this optimal length should be analyzed in trade-off studies for thrust loss versus gross vehicle weight. Plots of the oblique shock wave equations were also identified which will allow computation of slip line angle, dynamic pressure coefficient, or ambient Mach number for various specific heat ratios.

Shyne, Rickey J.↗

Approximate simulation model for analysis and optimization in engineering system design

Computational support of the engineering design process routinely requires mathematical models of behavior to inform designers of the system response to external stimuli. However, designers also need to know the effect of the changes in design variable values on the system behavior. For large engineering systems, the conventional way of evaluating these effects by repetitive simulation of behavior for perturbed variables is impractical because of excessive cost and inadequate accuracy. An alternative is described based on recently developed system sensitivity analysis that is combined with extrapolation to form a model of design. This design model is complementary to the model of behavior and capable of direct simulation of the effects of design variable changes.

Sobieszczanski-Sobieski, Jaroslaw↗

A Large-Scale Analysis to Optimize the Control and V2V Communication Protocols for CDA Agreement-Seeking Cooperation

Cooperative driving automation (CDA) Class C, agreement-seeking cooperation, is an innovative and practical solution that can promote cooperation among general passenger vehicles on the road. However, more comprehensive studies are needed before establishing the standard protocols of agreement-seeking cooperation, such as communication frequency and the duration of cooperation. Here, this article presents an initiative study on the impacts of communication capabilities on agreement-seeking cooperation. Through a large-scale analysis by regulating vehicle-to-vehicle (V2V) communication metrics, this work suggests desirable system parameters that can maximize the benefits of cooperation and ensure reliable operability while avoiding exhaustive communication loads. As the first step, an example agreement-seeking cooperation system is created for a car-following scenario, including decision-making and control algorithms for autonomous vehicles. Then, software-in-the-loop tests explore the performance of the developed system as it encounters various communication risks, such as latency and message packet drops. The system performance metrics are evaluated from various angles, including the time consumed for the agreement-seeking process, cooperation ratio, and the ratio of faulty cooperation. Energy saving from the cooperation is assessed by using simulation software that can run multiple high-fidelity vehicle models simultaneously. Based on the analyses, this article suggests the V2V communication requirements for the reliable operation of CDA agreement-seeking, which can be referred to when developing the standard protocols of agreement-seeking cooperation.

42 ENGINEERING↗

Optimization and Analysis of High-Power Hydrogen/Bromine-Flow Batteries for Grid-Scale Energy Storage

For storage of grid-scale electrical energy, redox-flow batteries (RFBs) are considered promising technologies. This paper explores the influence of electrolyte composition and ion transport on cell performance by using an integrated approach of experiments and cost modeling. In particular, the impact of the area-specific resistance on system capability is elucidated for the hydrogen/bromine RFB. The experimental data demonstrate very good performance with 1.46 W cm(-2) peak power and 4 A cm(-2) limiting current density at ambient conditions for an optimal cell design and reactant concentrations. The data and cost model results show that higher concentrations of RFB reactants do not necessarily result in lower capital cost as there is a tradeoff between cell performance and storage (tank) requirements. In addition, the discharge time and overall efficiency demonstrate nonlinear effects on system cost, with a 3 to 4 hour minimum discharge time showing a key transition to a plateau in terms of cost for typical RFB systems. The presented results are applicable to many different RFB chemistries and technologies and highlight the importance of ohmic effects and associated area-specific resistance on RFB viability.

Cho, KT↗

Crew Exploration Vehicle Ascent Abort Trajectory Analysis and Optimization

The Orion Crew Exploration Vehicle is the first crewed capsule design to be developed by NASA since Project Apollo. Unlike Apollo, however, the CEV is being designed for service in both Lunar and International Space Station missions. Ascent aborts pose some issues that were not present for Apollo, due to its launch azimuth, nor Space Shuttle, due to its cross range capability. The requirement that a North Atlantic splashdown following an abort be avoidable, in conjunction with the requirement for overlapping abort modes to maximize crew survivability, drives the thrust level of the service module main engine. This paper summarizes 3DOF analysis conducted by NASA to aid in the determination of the appropriate propulsion system for the service module, and the appropriate propellant loading for ISS missions such that crew survivability is maximized.

Falck, Robert D.↗

Description and Use of SCALE Sampler Parametric Capability for Engineering Analysis and Optimization

The Sampler sequence was introduced into the SCALE nuclear modeling and simulation suite in SCALE 6.2 to perform uncertainty quantification via random sampling of nuclear data, material number densities, and dimensions. Sampler was expanded with the introduction of a parametric capability in SCALE 6.2.2. This paper discusses input for the Sampler parametric sequence and presents two case studies of analyses performed using the sequence. These case studies include preconceptual design of a package for transporting high assay low-enriched uranium (HALEU) oxide and scoping calculations to support subcritical limit development for a future update of the ANSI/ANS-8.1 (ANS-8.1) standard. The parametric capability within Sampler provides many benefits to analysts. For instance, parametric sweeps are frequently used to identify optimum parameter values as part of safety analysis or system design, but such sweeps can require substantial engineering time or may rely on custom-written scripts or scripts such as Write One, Run Many (or WORM) developed outside of any software quality assurance program. With the parametric capabilities in Sampler, however, a large number of inputs can be generated automatically without recourse to scripting by individual analysts. The parametric capability can also be used in lieu of the CSAS5S search sequence to identify optimum parameters more simply with straightforward inputs and outputs. Sampler can also be used to calculate input parameters from engineering specifications. For example, diameters can be converted to radii, or masses can be used to calculate number densities. Overall, the Sampler parametric capability provides a robust feature within SCALE, eliminating the need for user-developed scripting.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Gamma-ray timing of redback PSR J2339–0533: Hints for gravitational quadrupole moment changes

We present the results of precision gamma-ray timing measurements of the binary millisecond pulsar PSR J2339–0533, an irradiating system of the “redback” type, using data from the Fermi Large Area Telescope. We describe an optimized analysis method to determine a long-term phase-coherent timing solution spanning more than six years, including a measured eccentricity of the binary orbit and constraints on the proper motion of the system. A major result of this timing analysis is the discovery of an extreme variation of the nominal 4.6 hr orbital period P{sub orb} over time, showing alternating epochs of decrease and increase. We inferred a cyclic modulation of P{sub orb} with an approximate cycle duration of 4.2 yr and a modulation amplitude of ΔP{sub orb}/P{sub orb}=2.3×10{sup −7}. Considering different possible physical causes, the observed orbital-period modulation most likely results from a variable gravitational quadrupole moment of the companion star due to cyclic magnetic activity in its convective zone.

79 ASTRONOMY AND ASTROPHYSICS↗

An innovative and advanced coupled neutron transport and thermal hydraulic method (tool) for the design, analysis and optimization of VHTR/NGNP prismatic reactors

This project will develop a 3D, advanced coarse mesh transport method (COMET-Hex) for steady- state and transient analyses in advanced very high-temperature reactors (VHTRs). The project will lead to a coupled neutronics and thermal hydraulic (T/H) core simulation tool with fuel depletion capability. The computational tool will be developed in hexagonal geometry, based solely on transport theory without (spatial) homogenization in complicated 3D geometries. In addition to the hexagonal geometry extension, collaborators will concurrently develop three additional capabilities to increase the code’s versatility as an advanced and robust core simulator for VHTRs. First, the project team will develop and implement a depletion method within the core simulator. Second, the team will develop an elementary (proof-of-concept) 1D time-dependent transport method for efficient transient analyses. The third capability will be a thermal hydraulic method coupled to the neutronics transport module for VHTRs. Current advancements in reactor core design are pushing VHTRs toward greater core and fuel heterogeneity to pursue higher burn-ups, efficiently transmute used fuel, maximize energy production, and improve plant economics and safety. As a result, an accurate and efficient neutron transport, with capabilities to treat heterogeneous burnable poison effects, is highly desirable for predicting VHTR neutronics performance. This research project’s primary objective is to advance the state of the art for reactor analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Conceptual Design Oriented Wing Structural Analysis and Optimization

Airplane optimization has always been the goal of airplane designers. In the conceptual design phase, a designer's goal could be tradeoffs between maximum structural integrity, minimum aerodynamic drag, or maximum stability and control, many times achieved separately. Bringing all of these factors into an iterative preliminary design procedure was time consuming, tedious, and not always accurate. For example, the final weight estimate would often be based upon statistical data from past airplanes. The new design would be classified based on gross characteristics, such as number of engines, wingspan, etc., to see which airplanes of the past most closely resembled the new design. This procedure works well for conventional airplane designs, but not very well for new innovative designs. With the computing power of today, new methods are emerging for the conceptual design phase of airplanes. Using finite element methods, computational fluid dynamics, and other computer techniques, designers can make very accurate disciplinary-analyses of an airplane design. These tools are computationally intensive, and when used repeatedly, they consume a great deal of computing time. In order to reduce the time required to analyze a design and still bring together all of the disciplines (such as structures, aerodynamics, and controls) into the analysis, simplified design computer analyses are linked together into one computer program. These design codes are very efficient for conceptual design. The work in this thesis is focused on a finite element based conceptual design oriented structural synthesis capability (CDOSS) tailored to be linked into ACSYNT.

Lau, May Yuen↗

Performance analysis and optimization for scalable deployment of deep learning models for country-scale settlement mapping on Titan supercomputer

Here, we present a scalable object detection workflow for detecting objects, such as settlements, from remotely sensed (RS) imagery. We have successfully deployed this workflow on Titan supercomputer and utilized it for the task of mapping human settlement at a country scale. The performance of various stages in the workflow was analyzed before making it operational. The workflow implemented various strategies to address issues such as suboptimal resource utilization and long-tail effects due to unbalanced image workload, data loss due to runtime failures, and maximum wall-time constraints imposed by Titan's job scheduling policy. A mean shift clustering–based static load balancing strategy was implemented, which partitions the image load such that each partition contained similar-sized images. Furthermore, a checkpoint-restart strategy was added in the workflow as a fault-tolerance mechanism to prevent the data losses due to unforeseen runtime failures. The performance of the above-mentioned strategies was observed in various scenarios, such as node failure, exceeding wall time, and successful completion. Using this workflow, we have examined an RS data set that has a spatial resolution of 0.31 m and is comprised of 685 675 km 2 of area of the Republic of Zambia in under six hours using 5426 nodes of the Titan supercomputer.

97 MATHEMATICS AND COMPUTING↗