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At least 649 records · Page 36

Method and Apparatus for Flight Data Acquisition using an Optimized Multiple Frequency Waveform

The present invention comprises a method and apparatus that generates a waveform consisting of an arbitrary number of frequency sweeps combined from adding and subtracting mini frequency sweeps. Optimization routines determine the best combination order of frequency sweep to minimize or maximize design criteria such is aerodynamic surface deflection or maximum command rate of the wave form. The invention allows for arbitrary output timing, or commands per second issued for the desired waveform, arbitrary starting and ending frequencies and amplitudes, arbitrary number of frequency sweep components, arbitrary frequency sweep exponent, arbitrary amplitude sweep exponent, and arbitrary waveform length. For a given frequency range and sweep exponent, amplitude range and sweep exponent, desired total waveform time and number of frequency sweep components, the algorithm can determine the optimum arrangement of the components to minimize the maximum amplitude or rate.

Bryan D Duke↗

Preliminary parameter studies to form pellets of hard materials for optical constants derived via single-angle reflectance spectroscopy

Infrared reflectance spectra can be influenced by many factors: the substrate and the thickness of the layer for liquids and the surface micromorphology, the form (powder, crystal) and the particle size for solids. All these parameters can play a role in the appearance of the measured spectrum. To avoid collecting multitudes of spectra to cover all such scenarios, the optical constants n and k, which are intrinsic properties of a material, can instead be used to model the reflectance spectrum. For solids, two techniques are often used to derive optical constants: ellipsometry and single-angle reflectance spectroscopy. For both methods, best results are usually obtained from single crystals. We have recently demonstrated for ammonium sulfate (a relatively soft material) that by optimizing certain conditions, high quality pellets with specularly reflective surfaces can be used in lieu of crystals. This was confirmed by the excellent agreement between the optical constants derived by these two methods. This work focuses on the possible extension of these methods to harder materials, starting with sodium sulfate. The first goal is to see if high quality pellet surfaces can be obtained as for ammonium sulfate. The reflectance values and the associated optical constants can also be obtained.

Diaz, Emmanuela↗

Towards Automated Generation of Chiplet-Based Systems

The Software Defined Architectures (SODA) Synthesizer is an open-source compiler-based tool able to automatically generate domain-specialized systems targeting Application- Specific Integrated Circuits (ASICs) or Field Programmable Gate Arrays (FPGAs) starting from high-level programming. SODA is composed of a high-level frontend, SODA-OPT, which leverages the multilevel intermediate representation (MLIR) framework to interface with productive programming tools (e.g., machine learning frameworks), identify kernels suitable for acceleration, and perform high-level optimizations, and of a state-of-the-art high-level synthesis backend, Bambu from the PandA framework, to generate custom accelerators. One specific application of the SODA Synthesizer is the generation of accelerators to enable ultra-low latency inference and control on autonomous systems for scientific discovery (e.g., electron microscopes, sensors in particle accelerators, etc.). This talk will discuss ongoing work on the SODA synthesizer to enable no-human-in-the-loop generation and design space exploration of the chiplets for highly specialized artificial intelligence accelerators. Connecting these highly specialized chiplets to general-purpose cores or programmable accelerators will allow to quickly deploy autonomous systems for scientific discovery.

Limaye, Ankur M.↗

Catalysts by pyrolysis: Direct observation of chemical and morphological transformations leading to transition metal-nitrogen-carbon materials

Transition metal-nitrogen-carbon materials (M-N-C catalysts) are promising electrocatalysts in polymer electrolyte fuel cells (PEFCs) and electrolyzer applications. High temperature treatment in inert atmosphere (pyrolysis) is the essential, most common method for the synthesis of M-N-C catalysts and critical to achieve high electrocatalytic activity and electronic conductivity. To this day, despite many uses and successful implementations in materials manufacturing, pyrolysis has been an entirely empirical technology, with process control and optimization relying exclusively on “Edisonian” approach. The knowledge gap in the mechanism about how the precursor is being transformed into catalysts hinders further development of the M-N-C catalysts regardless of the precursor class and processing protocols. In this work, we probed the morphological evolution and chemical transformation of a nitrogen-containing charge transfer organic salt, mixed with transition metal (iron) salt and amorphous silica powder (precursor) during the pyrolysis process via a combination of in situ synchrotron and laboratory-based diagnostic techniques. The pyrolysis process is found to be divided into three stages. During a controlled temperature ramp, the selected organic N-C precursor (nicarbazin) began melting and decomposing just below 400 °C, forming a certain number of micrometer-scale pores and pathways. With increase in temperature from 400 °C to 900 °C, amorphous carbon domains started forming, and reduced (metallic) iron nanoclusters appeared, being dispersed uniformly throughout the carbonaceous matrix. When temperature advanced above 900 °C, graphitization of carbon commenced, associated with appearance and evolution of atomically dispersed metal-nitrogen moieties in the carbonaceous matrix. As the graphitization advanced further, a secondary process of agglomeration of metal nanoparticles occurred. Multi-analytical technique observations conducted here provide a base for rational design and optimization of M-N-C electrocatalysts via pyrolysis.

36 MATERIALS SCIENCE↗

Digital Transformation for the Existing Fleet: Where to Start?

To remain economically viable in today’s electricity marketplace, nuclear power plants are replacing old analog equipment with modern digital tools. Having information available in an electronic format allows most work processes to become more efficient by automating simple, time-consuming tasks. However, with thousands of routine work processes performed every day, it can be difficult for the plants to know where to begin. We partnered with a nuclear utility to develop a novel assessment tool that measures seven health indicators for each work process performed, providing a rapid digital status report of the plant. The assessment tool is inexpensive and user-friendly, administered remotely, and automatically customized to each employee. Data from 167 employees representing different perspectives were analyzed to identify optimal candidates for digital initiatives that yield the highest payback for increased process efficiencies. We ranked by a priority index to ensure that processes with a good combination of time savings and digital opportunity were at the top. The focus was on determining a maximum investment to ensure that the cost savings from these initiatives are positive over a specified period. We identified potential cost savings of $2.6m, $1.3m and $1.2m for our top priority processes. By using our novel assessment tool to determine the digital status of the plant’s work processes, they were provided with a starting point for target candidates that would most benefit from a digital initiative. Our analysis helps stakeholders understand the financial impact of digital initiatives and identify maximum investment amounts when seeking technical solutions.

assessment↗

Flow analysis and design optimization methods for nozzle-afterbody of a hypersonic vehicle

This report summarizes the methods developed for the aerodynamic analysis and the shape optimization of the nozzle-afterbody section of a hypersonic vehicle. Initially, exhaust gases were assumed to be air. Internal-external flows around a single scramjet module were analyzed by solving the 3D Navier-Stokes equations. Then, exhaust gases were simulated by a cold mixture of Freon and Ar. Two different models were used to compute these multispecies flows as they mixed with the hypersonic airflow. Surface and off-surface properties were successfully compared with the experimental data. The Aerodynamic Design Optimization with Sensitivity analysis was then developed. Pre- and postoptimization sensitivity coefficients were derived and used in this quasi-analytical method. These coefficients were also used to predict inexpensively the flow field around a changed shape when the flow field of an unchanged shape was given. Starting with totally arbitrary initial afterbody shapes, independent computations were converged to the same optimum shape, which rendered the maximum axial thrust.

Baysal, O.↗

Climate drives modeled forest carbon cycling resistance and resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond to (resistance) and recover from (resilience) rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the Ecosystem Demography-2.2 (ED-2.2) model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900 (approximating the clear-cut conditions at the time), and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes such as gross primary production (GPP), and interacted with one another. We then calculated resistance and resilience, two dimensions of ecosystem stability. Modeled GPP exhibited a two-fold decrease in mean resistance across disturbance severities of 45%, 65%, and 85% mortality; conversely, resilience increased by a factor of two with increasing disturbance severity. This pattern held for net primary production and net ecosystem production, indicating a trade-off in which greater initial declines were followed by faster recovery. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

Kalyn Dorheim↗

Climate drives modeled forest carbon cycling resistance and resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond to (resistance) and recover from (resilience) rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the Ecosystem Demography-2.2 (ED-2.2)model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900(approximating the clear-cut conditions at the time),and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes such as gross primary production (GPP),and interacted with one another. We then calculated resistance and resilience, two dimensions of ecosystem stability. Modeled GPP exhibited a two-fold decrease in mean resistance across disturbance severities of 45%, 65%, and 85% mortality; conversely, resilience increased by a factor of two with increasing disturbance severity. This pattern held for net primary production and net ecosystem production, indicating a trade-off in which greater initial declines were followed by faster recovery. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

Kalyn Dorheim↗

A Surrogate-Based Asynchronous Decomposition Technique for Realistic Security-Constrained Optimal Power Flow Problems

Here we present a decomposition approach for obtaining good feasible solutions for the security-constrained, alternating-current, optimal power flow (SC-AC-OPF) problem at an industrial scale and under real-world time and computational limits. The approach was designed while preparing and participating in ARPA-E’s Grid Optimization Competition (GOC) Challenge 1. The challenge focused on a near-real-time version of the SC-AC-OPF problem, where a base operating point is optimized, taking into account possible single-element contingencies, after which the system adapts its operating point following the response of automatic frequency droop controllers and voltage regulators. Our solution approach for this problem relies on state-of-the-art nonlinear programming algorithms, and it employs nonconvex relaxations for complementarity constraints, a specialized two-stage decomposition technique with sparse approximations of recourse terms and contingency ranking and prescreening. The paper describes and justifies our approach and outlines the features of its implementation, including functions and derivatives evaluation, warm-starting strategies, and asynchronous parallelism. We discuss the results of the independent benchmark of our approach by ARPA-E’s GOC team in Challenge 1, where it was found to consistently produce high-quality solutions across a wide range of network sizes and difficulty, and conclude by outlining future extensions of the approach.

97 MATHEMATICS AND COMPUTING↗

Shuttle cryogenic supply system optimization study. Volume 5A-2: Users manual for Space shuttle orbit injection system analysis (SOPSA)

SOPSA (Shuttle Orbit Injection Propulsion System Analysis) is a computer program to aid in the preliminary design of propellant feed systems for the space shuttle orbiter main engines. The primary purpose of the program is to evaluate propellant tank ullage pressure requirements imposed by the need to accelerate propellants rapidly during the engine start sequence. These requirements can influence the system design for a given engine as well as the suitability of a given system for use with different engines. During the vehicle design phase, the SOPSA program is used to establish feed system weight variations as a function of nominal line diameter and component and line configurations. The weight data are used in conjunction with pertinent cost data to establish optimum feed system designs.

Source record↗

An optimized ChIP-Seq framework for profiling histone modifications in Chromochloris zofingiensis

The eukaryotic green alga Chromochloris zofingiensis is a reference organism for studying carbon partitioning and a promising candidate for the production of biofuel precursors. Recent transcriptome profiling transformed our understanding of its biology and generally algal biology, but epigenetic regulation remains understudied and represents a fundamental gap in our understanding of algal gene expression. Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a powerful tool for the discovery of such mechanisms, by identifying genome-wide histone modification patterns and transcription factor-binding sites alike. Here, we established a ChIP-Seq framework for Chr. zofingiensis yielding over 20 million high-quality reads per sample. The most critical steps in a ChIP experiment were optimized, including DNA shearing to obtain an average DNA fragment size of 250 bp and assessment of the recommended formaldehyde concentration for optimal DNA-protein cross-linking. We used this ChIP-Seq framework to generate a genome-wide map of the H3K4me3 distribution pattern and to integrate these data with matching RNA-Seq data. In line with observations from other organisms, H3K4me3 marks predominantly transcription start sites of genes. Our H3K4me3 ChIP-Seq data will pave the way for improved genome structural annotation in the emerging reference alga Chr. zofingiensis.

59 BASIC BIOLOGICAL SCIENCES↗

LightMAT - Continuous fiber malleable thermoset composites with sub-1-minute dwell times; validation of impact performance and evaluation of the efficacy of the compression forming process (CRADA 409 Final Report)

In spite of carbon fiber composite materials’ significant impact on light-weighting, performance, and efficiency in the aerospace industry, adoption of these materials has been slow in high-volume industries such as automotive. Two major barriers to adoption are cost and cycle-time. Current approaches to thermoset composite part production are dependent on in-mold curing of thermosets which are not optimal for high volume, high throughput production due to limitations and inefficiencies associated with the in-mold cure itself. In addition, ancillary activities, such as transport and storage of shelf-life-limited uncured, or B-staged prepreg materials typically necessitate refrigerated transport and storage which significantly impacts the economic and energy costs associated with manufacturing. Furthermore, limited out-life means that trimmings cannot typically be used as they partially cure during initial production leading to high scrap rates (+20% is common). Finally, the need to cure in-mold drives cycle times to multiple minutes in the best cases, and 10’s of minutes to hours in most cases. Mallinda is developing polyimine malleable thermoset prepreg composite materials which have excellent mechanical properties (100 GPa tensile modulus, 2 GPA tensile strength, 2.4% elongation at break) and high operating temperatures (Tg>200°C). At scale, polyimine resins are commensurate in price with commodity epoxy resins. What distinguishes malleable thermoset prepreg from traditional thermoset prepreg materials, is that they are fully cured during Mallinda’s roll-to-roll production of prepreg laminate. This results in 5 key value-differentiating benefits. First, it simplifies manufacturing logistics by enabling ambient transportation and storage, and by significantly extending out-life and shelf-life almost indefinitely. Second, elimination of autoclave curing reduces the economic and energy costs to the customer. Third, scrap rates can be reduced as malleable thermoset prepreg materials are directly reusable. Fourth, the manufacturing consolidation step can be roughly 10x faster than traditional thermosets, because the resin is already cured. Parts can be made via compression forming by the application of heat and pressure to quickly vitrify and consolidate a multilayer part – easily leading to sub 3-minute cycle times (at lab scale we have demonstrated a 20 second dwell time, with room for further optimization). Finally, the closed-loop cradle-to-cradle solution-based recyclability of malleable thermoset composites can also contribute significantly to the future of sustainable lightweight materials. The focus of this project was the development, optimization and validation of malleable thermoset composite materials which exhibit manufacturing cycle times of 3-minute or less, high speed impact performance on par with incumbent technologies, and defect-free consolidation of 3 dimensional parts. Government funding is required on this project because Mallinda is a start-up company whose focus is the development and scale-up of the described technology for introduction to the transportation segment. Unlike incumbent industry players, Mallinda is bringing a completely new and highly relevant malleable thermoset technology to bear on the problem of high throughput composites. As a small business, Mallinda relies on a combination of government R&D funding and private capital to perform development work.

36 MATERIALS SCIENCE↗

Development of ~25% Efficient Double Side Screen Printed Poly-Si/SiO x Passivated Contact Solar Cells

This program aims to overcome these challenges and develop high-efficiency (24-25%) double-side (DS) TOPCon solar cells by maximizing passivation on both sides while mitigating light absorption losses. To achieve this, the program will implement either thin (≤ 20 nm) homogeneous n-TOPCon on the entire front surface or selective area thick (≥ 100 nm) n-TOPCon only underneath the front metal contact with ~90% field region composed of dielectric passivated textured n-Si in between the poly-Si/metal grid. The rear side will feature ~250 nm-thick full-area planar p-TOPCon, which functions as the rear junction. Recombination and parasitic absorption losses in the front and rear TOPCon layers will be minimized by tailoring their doping profiles and thickness. Additionally, the device performance will be further enhanced through the optimization of bulk parameters, including the carrier lifetime, resistivity, and thickness of the n-type Si absorber. Finally, advanced metallization techniques, such as fine-line printing, and floating busbar or busbar-less designs, will be employed to reduce recombination, resistive, and optical losses. The program started with the development of a technology roadmap for DS-TOPCon cells to achieve target efficiency.

14 SOLAR ENERGY↗

Friction and wear results from sputter-deposited chrome oxide with and without nichrome metallic binders and interlayers

Friction and wear tests were conducted on optimized sputtered Cr2O3 and Cr2O3 with metallic binder coatings. The coatings were applied on the bearing surface of journal foil air bearings and were tested against chrome-carbide-coated journal surfaces. The objective of the study was to develop a coating system which would withstand 9000 start-stops and high-speed rubs (maximum acceleration, 100 gs) in temperatures ranging from room temperature to 650 C. The Cr2O3 coating completed the test sequence and the coating consisting of Cr2O3 with metallic binders completed 3000 start-stops. The coefficient of friction of the coatings at 650 C was found to be about half that at room temperature. It was concluded, therefore, that the coatings should perform much better in a high temperature environment alone. The decrease in friction at high temperature is attributed to oxidation and interactions of the coatings and substrates at the interface temperature.

Bhushan, B.↗

Performance tradeoffs in static and dynamic load balancing strategies

The problem of uniformly distributing the load of a parallel program over a multiprocessor system was considered. A program was analyzed whose structure permits the computation of the optimal static solution. Then four strategies for load balancing were described and their performance compared. The strategies are: (1) the optimal static assignment algorithm which is guaranteed to yield the best static solution, (2) the static binary dissection method which is very fast but sub-optimal, (3) the greedy algorithm, a static fully polynomial time approximation scheme, which estimates the optimal solution to arbitrary accuracy, and (4) the predictive dynamic load balancing heuristic which uses information on the precedence relationships within the program and outperforms any of the static methods. It is also shown that the overhead incurred by the dynamic heuristic is reduced considerably if it is started off with a static assignment provided by either of the other three strategies.

Iqbal, M. A.↗

A comparative analysis of static and dynamic load balancing strategies

The problem of uniformly distributing the load of a parallel program over a multiprocessor system was considered. A program was analyzed whose structure permits the computation of the optimal static solution. Then four strategies for load balancing were described and their performance compared. The strategies are: (1) the optimal static assignment algorithm which is guaranteed to yield the best static solution, (2) the static binary dissection method which is very fast but suboptimal, (3) the greedy algorithm, a static fully polynomial time approximation scheme, which estimates the optimal solution to arbitrary accuracy, and (4) the predictive dynamic load balancing heuristic which uses information on the precedence relationships within the program and outperforms any of the static methods. It is also shown that the overhead incurred by the dynamic heuristic is reduced considerably if it is started off with a static assignment provided by either of the three strategies.

Iqbal, M. Ashraf↗

Earth Observing Scanning Polarimeter (EOSP), phase B

Evaluations performed during a Phase B study directed towards defining an optimal design for the Earth Observing Scanning Polarimeter (EOSP) instrument is summarized. An overview of the experiment approach is included which provides a summary of the scientific objectives, the background of the measurement approach, and the measurement method. In the instrumentation section, details of the design are discussed starting with the key instrument features required to accomplish the scientific objectives and a system characterization in terms of the Stokes vector/Mueller matrix formalism. This is followed by a detailing of the instrument design concept, the design of the individual elements of the system, the predicted performance, and a summary of appropriate instrument testing and calibration. The selected design makes use of key features of predecessor polarimeters and is fully compatible with the Earth Observing System spacecraft requirements.

Source record↗

Program Model Checking: A Practitioner's Guide

Program model checking is a verification technology that uses state-space exploration to evaluate large numbers of potential program executions. Program model checking provides improved coverage over testing by systematically evaluating all possible test inputs and all possible interleavings of threads in a multithreaded system. Model-checking algorithms use several classes of optimizations to reduce the time and memory requirements for analysis, as well as heuristics for meaningful analysis of partial areas of the state space Our goal in this guidebook is to assemble, distill, and demonstrate emerging best practices for applying program model checking. We offer it as a starting point and introduction for those who want to apply model checking to software verification and validation. The guidebook will not discuss any specific tool in great detail, but we provide references for specific tools.

Pressburger, Thomas T.↗