Search NASA⌕ Search

SEARCH · Search NASA

Results for “Complex Loading”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Spall strength of additively repaired 304L stainless steel

Additive manufacturing has the potential to repair damaged parts, but the performance of additive materials under high strain rate loading is still uncertain—especially with the added complexity of an interface with an existing wrought material. In this work, 304L stainless steel samples were intentionally damaged and then repaired with wire-fed laser additive manufacturing. The samples were subjected to shock loading to generate incipient spall. Velocimetry and post-mortem metallography results show that when the additive repair process parameters are optimized to reduce porosity and match the equation of state of the original material, the influence of the repair region on the shock propagation is negligible. In conclusion, the free-surface velocity profile and internal damage morphology of the repaired sample are shown to be practically identical to the pristine material.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

Digitally enhanced services for wind power could reduce Operations and Maintenance costs as well as the Levelised Cost Of Energy. Therefore, there is a continuous need for advanced monitoring techniques which can exploit the opportunities of Internet of Things and Big Data Analytics. The heart of wind turbines is an epicyclic gearbox and rolling element bearings are often responsible for machinery stops. The vibration signatures of bearings are rather weak compared to other components. As a result a number of signal processing techniques have been proposed, focusing towards accurate and early fault detection with limited false alarms and missed detections. In Envelope Analysis an envelope of the vibration signal is estimated usually after filtering around a frequency band. Different tools, such as Kurtogram, have been proposed to select the optimum filter parameters. Monitoring techniques have reached a mature level for steady speed and load operating conditions. On the other hand, under chaniging operating conditions, it is still unclear whether the change of the monitoring indicators is due to the change of the machinery's health or due to the change of operating parameters. Recently, the authors have proposed a new tool called IESFOgram, based on Cyclic Spectral Coherence for the automatic selection of the filtering band. In this paper, the performance of the tool is evaluated on the National Renewable Energy Laboratory wind turbine gearbox vibration condition monitoring benchmarking data set which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.

17 WIND ENERGY↗
DOE OSTI2023

PipeSight: A High-Performance Computing Platform for Pipeline Integrity Management

The Phase I feasibility study completed as part of this project has led to a number of innovative technologies being developed and has laid the foundation for a successful Phase II effort to commercialize a platform for managing the integrity of pipelines for the damage mechanisms of the new, hybrid-energy based economy. To ground the development efforts and direction of the project, an extensive market research and customer discovery effort was undertaken early in Phase I. Through this effort, a number of pipeline owners and operators were interviewed, and the following key findings were discovered about the pipeline industry: • Small pipeline operators do not have the central engineering groups necessary to perform their own independent analysis of inspection data, but instead rely on summarized tally sheets provided to them by inspection service providers. • The time it takes to go from an inspection to a completed engineering assessment, even for small segments of pipeline, can take anywhere from 30-120 days. During this delay, critical threats can (and have been known to) cause failures. • Uncertainty is often not accounted for in the assessment of pipeline integrity. The tally sheets provided by third-party service providers are almost always deterministic in nature, identifying threats that present a concern only to the current (not the future) integrity of the pipeline. • It is uncommon to apply the latest technologies to perform advanced assessments of damaged pipelines. There is a desire to use more advanced analysis capabilities to assess threats. Many pipeline operators indicated that they would often excavate a pipeline to perform an inspection and find that the damage was not as bad as they anticipated, thus using limited resources unnecessarily. Companies are not consistent in their use of inspection data to determine corrosion rates, and those that do only calculate deterministic corrosion rates. • The industry has prominently relied on time-based inspections but has recently started to transition to risk-based inspections. However, there appears to be no uniform guidance on how to do so while properly accounting for all sources of uncertainty. • Companies are not storing inspection data in a manner that allows for the ready determination of temporal trends. • Predictive maintenance principles and practices are beginning to be used by early adopters • Some pipelines are being re-purposed to transport different process fluids than they were designed for, e.g., H 2 and CO 2 rich process streams to serve the new hybrid-energy based economy, which are presenting new integrity concerns for the existing pipeline network that crisscrosses the United States. As a result of these discoveries, we were able to target the development efforts in Phase I to best serve the needs of the industry. In Phase I, we developed a way to correlate multiple large-scale scans of the pipeline to determine a probabilistic corrosion rate that accounts for all sources of error and uncertainty in the inspection process. This probabilistic corrosion rate can be used to predict the future thickness distribution of the pipe wall. We demonstrate how this analysis may be performed in an analytical fashion and has been implemented in such a manner that it can be readily distributed using GPU computing through integration of the Kokkos programming model. We also make a very novel extension of the analytical corrosion rate model to Bayesian Networks (an explainable AI technique) that can account for non-parametric distributions of corrosion rates. With the predictions made above for the probabilistic corrosion rate and corresponding future distribution of the pipe wall thickness, we can assess the integrity of the pipeline through the use of a probabilistic engineering assessment. We developed a novel screening data analysis approach that can rapidly identify ‘hotspots’ (local thin areas) where the integrity of the pipeline is a concern. Once more, we implemented this screening approach in C++ to leverage GPU computing via the Kokkos programming model. After the critical hotspots are identified, we developed a program that can automatically generate an advanced finite element model of the damaged regions. Since the number of damaged regions that require advanced analysis can number in the thousands, we integrated an open-source container-native workflow engine for orchestrating parallel jobs on the cloud. Initially, these advanced numerical models were only designed to account for loading due to internal pressure. However, in a slight pivot from the initial Phase I proposal, we developed a complete pipe stress analysis program (called Simflex) which can simulate the complete pipeline and its response to thermal expansion, pressure, thermal bowing, weight, wind, earthquake, support displacement, support friction and external forces. This pipe stress analysis program was written generically, to handle any piping system, but contains the features needed to model long pipelines (i.e., it incorporates a model for soil mechanics and can account for the nonlinear boundary conditions necessary to simulate long underground pipelines). This pipe stress analysis program can simulate any segment of the pipeline (simple or complex) under any set of conditions and loads, to determine the supplemental loads (axial forces and bending moments) at the location of damage. This enables the most accurate state of stress to be accounted for in the pipeline, which can prove critical when evaluating the integrity of a damaged region. In the process of developing the technologies to perform the integrity assessment of the pipeline, we also extended one of the industry standard approaches for performing the assessment of local thin areas that extend more in the circumferential direction than the longitudinal direction of the pipeline. This approach was presented to the API 579-1/AS ME FFS-1 steering committee in November 2021 for consideration in the next edition of the industry standard for Fitness-For-Service (expected to be released in 2023). To help pipeline operators make decisions with the results on any integrity assessment, we developed a new approach to the life-cycle management of pipelines which uses a Bayesian Decision Network. The network is designed to help pipeline operators plan and prioritize inspection activities and ultimately make smarter, more cost-effective decisions. The Bayesian approach accounts for all sources of uncertainty and carries them through to the final optimal decisions, providing a probabilistic framework for optimizing inspection intervals. The proof-of-concept networks developed in the feasibility study are complete, verified, and are focused on a subset of the pipeline. To expand this novel approach to the scale necessary for an entire network of pipelines in Phase II, we will leverage the DOE-funded Bengi solver for industrial-scale decision making with Bayesian Networks [22]. Once implemented, we will be able to provide the pipeline industry with a much-needed tool for optimal inspection planning using truly explainable artificial intelligence (XAI). To handle all of these advanced capabilities into a cloud-based platform, the architecture of the Equity Engineering Cloud (EEC) was extended to include Argo Workflows, a framework capable of distributing and managing a massive number of jobs that consume their own resources, such that thousands of serial finite element simulations can be run in parallel. As part of this substantial undertaking, we also integrated Argo Continuous Delivery (CD) into the EEC, to aid with the rapid prototyping and iterations that will be imperative to the success of the PipeSight platform’s Agile development process in Phase II. As part of the pipe stress analysis program, we also developed a custom visualizer that leverages the DOE-funded VTK visualization library. We added custom contouring capabilities and a means for interacting visually with both the inputs and outputs of the pipe stress analysis program. We also developed routines for automating the post-processing of the finite element simulations to determine if any failure criteria are met and to visualize the deformations, stresses and strains in ParaView using the exodus II file format (a subset of netCDF).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

An unusual Co–S bond links B 12 chaperones in an interprotein complex

Chaperones in trafficking pathways ensure specificity of transition metal loading and protection against adventitious side reactions. In B 12 , an essential cofactor for humans, a cobalt ion is coordinated to a >1.3 kDa tetrapyrrolic scaffold, posing logistical challenges for its translocation. In this study, we report the 3.4 Å crystal structure of the human MMACHC and MMADHC B 12 chaperones, tethered via a rarely seen covalent cobalt–sulfur bond. B 12 is bound in the base-off state to MMACHC, with Cys-261 on MMADHC serving as the upper axial ligand; the lower-axial position is vacant. The propensity of thiolato-cobalamin derivatives bound to MMACHC to undergo spontaneous decomposition via general acid catalysis or reduction/oxidation chemistry is averted in the interprotein complex with MMADHC. An exposed face in the complex suggests an exit route for B 12 . No known clinical variants localize to the interprotein interface, consistent with the cobalt–sulfur bond being key to forming the high-affinity complex.

Science & Technology - Other Topics↗
DOE OSTI2020

Design Considerations for High-Voltage Insulated Gate Drive Power Supply for 10-kV SiC MOSFET Applied in Medium-Voltage Converter

High-performance gate drive power supply (GDPS) plays a crucial role in ensuring the reliability and safety of the gate driver for power semiconductor devices. This article focuses on the design of a high-voltage-insulated GDPS for the 10-kV silicon carbide MOSFET in medium-voltage (MV) application. Design considerations, including insulation scheme, high-voltage-insulated transformer design, and load voltage regulation scheme, are proposed. In addition, the performance of the secondary-side-regulated (SSR) GDPS and that of the primary-side-regulated (PSR) GDPS are compared for several aspects, including interwinding capacitance, load voltage regulation rate, conversion efficiency, and hardware complexity. Finally, an SSR GDPS and a PSR GDPS, with an insulation voltage of 20 kV, are built in the lab. Furthermore, the test results demonstrate that the PSR GDPS is more preferable because of lower interwinding capacitance, lower load voltage regulation rate, higher conversion efficiency, and simpler control circuit.

42 ENGINEERING↗
DOE OSTI2024

Enhancing Distribution System Resilience: A First-Order Meta-RL Algorithm for Critical Load Restoration

The increasing frequency of extreme events and the integration of distributed energy resources (DERs) into modern grids have elevated the need for resilient and efficient critical load restoration strategies in distribution systems. However, the stochastic nature of renewable DERs, limited energy resource availability and the intricate nonlinearities inherent in complex grid control problem make the problem challenging. Although reinforcement learning (RL) and warm-start RL methods have shown promising results, their performance often falls short in rapidly adapting to new, unseen situations and typically requires exhaustive problem-specific tuning. To address these gaps, we propose a First-Order Meta-based RL (FOM-RL) algorithm within an online framework for adaptive and robust critical load restoration. By harnessing local DERs as the enabling technology, FOM-RL allows the RL agent to swiftly adapt to new unseen scenarios by leveraging previously acquired knowledge of different tasks. Experimental results provide evidence that proposed algorithm learns more efficiently and showcases generalization capabilities across diverse set of operational scenarios. Moreover, a rigorous theoretical analysis yields a tight sublinear regret bound, sensitive to temporal variability, with a task-averaged optimality gap bounded by O(VM+D*/(Tsquare root(M))). These results suggest that optimality improves with task similarity and an increased number of tasks M, reaffirming the efficacy and scalability of the proposed approach in addressing the complexities of critical load restoration in distribution systems.

complexity theory↗
DOE OSTI2018

Scalable Cloning on Large-Scale GPU Platforms with Application to Time-Stepped Simulations on Grids

Cloning is a technique to efficiently simulate a tree of multiple what-if scenarios that are unraveled during the course of a base simulation. However, cloned execution is highly challenging to realize on large, distributed memory computing platforms, due to the dynamic nature of the computational load across clones, and due to the complex dependencies spanning the clone tree. In this paper, we present the conceptual simulation framework, algorithmic foundations, and runtime interface of CloneX, a new system we designed for scalable simulation cloning. It efficiently and dynamically creates whole logical copies of a dynamic tree of simulations across a large parallel system without full physical duplication of computation and memory. The performance of a prototype implementation executed on up to 1,024 graphical processing units of a supercomputing system has been evaluated with three benchmarks—heat diffusion, forest fire, and disease propagation models—delivering a speed up of over two orders of magnitude compared to replicated runs. Finally, the results demonstrate a significantly faster and scalable way to execute many what-if scenario ensembles of large simulations via cloning using the CloneX interface.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Significance of Dynamic and Transient Analysis in the Design and Operation of Hybrid Energy Systems

Energy systems were historically designed and operated with a specific energy conversion objective, while managing loads and resources. In the recent years, the increased utilization of non-dispatchable renewable sources such as wind and solar has played a role in power quality and the reliability of power systems. In order to mitigate the risk associated with the non-dispatchable resources an integrated approach, such as Hybrid Energy Systems (HES), has to be taken, integrating the loads and resource management between the traditional thermal power plants and the non-dispatchable resources. As our electric energy becomes more diverse in its generation resources, the HES with its operational control system, its real-time view and its dynamic decisions making will become an essential part of the integrated energy systems and improve the overall grid reliability. The operational constraints of the energy sources on both the thermal power plants and the non-dispatchable resources in HES, plays a vital role in the planning and design stage. It is an established fact that the choice of energy source depends on the available natural resources and possible infrastructure. A critical component of decision-making depends on the complementary nature and controllability of the energy sources to supply the load demands with high reliability. Controllability of complex HES to achieve desired performance and flexibility is implemented via coordinated control systems while simultaneously generating electricity and other useful products such as useful heat or hydrogen. These systems are based on instrumentation, signal processing, control theory, and engineering system design. The entire HES along with the control systems are characterized by widely varying time constants. Hence, for a well-coordinated control and operation, we propose physics based modeling of the subsystems to assist in a dynamic and transient analysis. Dynamic and transient analysis in real and non-real time domain of the potential sources is capable of providing satisfactory results at the feasibility analysis stage. A simplified HES consisting of complementary energy sources is used to demonstrate the proposed approach. Suitable real time simulations to perform dynamic and transient analysis will be performed to verify results from the non-real time analysis. The role of such analyses, especially the real time dynamic and transient analysis for manual controls is elaborated. It is also discussed that faster than real time simulation will pave the future for controller rooms and hence manual control procedures. Multiple tools such as Real Time Simulator, Matlab®, Simulink®, PSCAD®, MOOSE, etc. are expected to be used for the HES analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Bimodal Nickel-Binding Site on Escherichia coli [NiFe]-Hydrogenase Metallochaperone HypA

[NiFe]-hydrogenase enzymes catalyze the reversible oxidation of hydrogen at a bimetallic active site and they are used by bacteria and archaea for anaerobic growth and pathogenesis. Maturation of the [NiFe]-hydrogenase requires several accessory proteins to assemble and insert the components of the active site. The penultimate maturation step is the delivery of nickel to a primed hydrogenase enzyme precursor protein, a process that is accomplished by two nickel metallochaperones, the accessory protein HypA and the GTPase HypB. Recent work demonstrated that nickel is rapidly transferred to HypA from GDP-loaded HypB within the context of a protein complex in a nickel selective and unidirectional process. To investigate the mechanism of metal transfer, we examined the allosteric effect of nucleotide cofactors and partner-proteins on the nickel environments of HypA and HypB by using a combination of biochemical, microbiological, computational, and spectroscopic techniques. We observed that loading HypB with either GDP or a non-hydrolyzable GTP analogue resulted in a similar nickel environment. In addition, interaction with a mutant version of HypA with disrupted nickel binding, H2Q-HypA, does not induce substantial changes to the HypB G-domain nickel site. Instead, the results demonstrate that HypB modifies the acceptor site of HypA. Analysis of a peptide maquette derived from the N-terminus of HypA revealed that nickel is predominately coordinated by atoms from the N-terminal Met-His- motif. Furthermore, HypA is capable of two nickel-binding modes at the N-terminus, a HypB-induced mode and a binding mode that mirrors the peptide maquette. Collectively, these results reveal that HypB brings about changes in the nickel coordination of HypA, providing a mechanism for the HypB-dependent control of the acquisition and release of nickel by HypA.

08 HYDROGEN↗
DOE OSTI2015

Floating Offshore WTG Integrated Load Analysis & Optimization Employing a Tuned Mass Damper

Floating offshore wind turbines (FOWTs) present complex design challenges due to the coupled dynamics of the platform motion, mooring system, and turbine control systems, in response to wind and wave loading. This can lead to higher extreme and fatigue loads than a comparable fixed bottom or onshore system. Previous research[1] has shown the potential to reduced extreme and fatigue loads on FOWT using tuned mass dampers (TMD) for structural control. This project aims to reduce maximum loads using passive TMDs located at the tower top during extreme storm events, when grid supplied power for other controls systems may not be available. The Alstom Haliade 6MW wind turbine is modelled on the Glosten Pelastar tension-leg platform (TLP). The primary objectives of this project are to provide a preliminary assessment of the load reduction potential of passive TMDs on real wind turbine and TLP designs.

17 WIND ENERGY↗
DOE OSTI2016

Pillar[5]arene Based Conjugated Microporous Polymers for Propane/Methane Separation through Host–Guest Complexation

We present an efficient strategy for the preparation of conjugated microporous polymers incorporating pillar[5]arenes (P5-CMPs) with surface areas up to 400 m 2 g –1 via Pd-catalyzed Sonogashira–Hagihara cross-coupling reaction of triflate functionalized pillar[5]arene with 1,4-diethynylbenzene and 4,4'-diethynyl-1,1'-biphenyl linkers. In an effort to transfer intrinsic properties of pillar[5]arene, that is its ability to form strong host–guest complexes with linear hydrocarbons in solution, into the solid-state, we investigated the affinity of P5-CMPs toward propane gas. Unlike previously reported porous solids, which showed isosteric heats of adsorption ($Q$ st ) for propane in the range of 32.9–36.9 kJ mol–1 at zero coverage and increasing $Q$ st with rising loading due to intermolecular interactions between propane molecules, we observed very high $Q$ st values up to 53 kJ mol –1 at zero coverage, which gradually decreased to ~35 kJ mol –1 with increasing loadings. This observation indicates strong supramolecular host–guest complexation between propane and pillar[5]arene via multiple C–H/$π$ interactions, i.e., “macrocyclic effect” arising from the ideal size match of kinetic diameter of propane to the cavity of pillar[5]arene. This approach also allowed us to introduce thermodynamic selectivity for the separation of saturated hydrocarbons with low polarizability. High affinity of P5-CMPs for propane facilitated its efficient breakthrough separation from a simulated natural gas mixture (methane:propane, 9:1) at 298 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Therapeutic Potential of DNAzyme Loaded on Chitosan/Cyclodextrin Nanoparticle to Recovery of Chemosensitivity in the MCF-7 Cell Line

Commonly, acquired resistances to anticancer drug are mediated by overexpression of a membrane-associated protein that encode via multi-drug resistance gene-1 (MDR1). Herein, the mRNA-cleaving DNAzyme that targets the mRNA of MDR1 gene in doxorubicin-resistant breast cancer cell line (MCF-7/DR) loaded on the chitosan β-cyclodextrin complexes was used as a tropical agent. Chitosan/β-cyclodextrin complexes were used to deliver DNAzymes into cancer cells. Determination of the physicochemical characteristics of the particles was done by photon correlation spectroscopy and scanning electron microscopy. The encapsulation efficiency of the complexes was tested by using gel retardation assay. Positively charged nanoparticles interacted with DNAzyme that could perform as an efficient DNAzyme transfection system. The rationale usage of this platform is to sensitize MCF-7/DR to doxorubicin by downregulating the drug-resistance gene MDR1. Results demonstrated a downregulation of MDR1 mRNAs in MCF-7/DR/DNZ by real-time PCR, compared to the MCF-7/DR as control. WST1 assay showed the 22-fold decrease in drug resistance on treated cells 24 h after transfection. Results showed the intracellular accumulation of Rh123 increased in the treated cells with DNAzyme. Results suggested a potential platform in association with chemotherapy drug for cancer therapy and indicated extremely efficient at delivery of DNAzyme in restoring chemosensitivity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Multidomain Convergence of Argonaute during RISC Assembly Correlates with the Formation of Internal Water Clusters

Despite the relevance of Argonaute proteins in RNA silencing, little is known about the structural steps of small RNA loading to form RNA-induced silencing complexes (RISCs). We report the 1.9 Å crystal structure of human Argonaute4 with guide RNA. Comparison with the previously determined apo structure of Neurospora crassa QDE2 revealed that the PIWI domain has two subdomains. Binding of guide RNA fastens the subdomains, thereby rearranging the active-site residues and increasing the affinity for TNRC6 proteins. We also identified two water pockets beneath the nucleic acid-binding channel that appeared to stabilize the mature RISC. Indeed, mutating the water-pocket residues of Argonaute2 and Argonaute4 compromised RISC assembly. Simulations predict that internal water molecules are exchangeable with the bulk solvent but always occupy specific positions at the domain interfaces. These results suggest that after guide RNA-driven conformational changes, water-mediated hydrogen-bonding networks tie together the converged domains to complete the functional RISC structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Cobalt-Catalyzed Hydrogenation Reactions Enabled by Ligand-Based Storage of Dihydrogen

The use of supporting ligands that can store either protons or electrons has emerged as a powerful strategy in catalysis. While these strategies are potent individually, natural systems mediate remarkable transformations by combining the storage of both protons and electrons in the secondary coordination sphere. As such, there has been recent interest in using this strategy to enable fundamentally different transformations. Furthermore, outsourcing H-atom or hydrogen storage to ancillary ligands can also enable alternative mechanistic pathways and thereby selectivity. Here, we describe the application of this strategy to facilitate radical reactivity in Co-based hydrogenation catalysis. Metalation of previously reported dihydrazonopyrrole ligands with Co results in paramagnetic complexes, which are best described as having Co(II) oxidation states. These complexes catalytically hydrogenate olefins with low catalyst loadings under mild conditions (1 atm H 2 , 23 °C). Mechanistic, spectroscopic, and computational investigations indicate that this system goes through a radical hydrogen-atom transfer (HAT) type pathway that is distinct from classic organometallic mechanisms and is supported by the ability of the ligand to store H 2 . These results show how ancillary ligands can facilitate efficient catalysis, and furthermore how classic organometallic mechanisms for catalysis can be altered by the secondary coordination sphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Geometrically projected discrete dislocation dynamics

Three-dimensional discrete dislocation dynamics methods (3D-DDD) have been developed to explicitly track the motion of individual dislocations under applied stress. At present, these methods are limited to plastic strains of about one percent or less due to high computational cost associated with the interactions between large numbers of dislocations. This limitation motivates the construction of minimalistic approaches to efficiently simulate the motion of dislocations for higher strains and longer time scales. In the present study, we propose geometrically projected discrete dislocation dynamics (GP-DDD), a method in which dislocation loops are modeled as geometrical objects that maintain their shape with a constant number of degrees of freedom as they expand. We present an example where rectangles composed of two screw and two edge dislocation segments are used for modeling gliding dislocation loops. We use this model to simulate single slip loading of copper and compare the results with detailed 3D-DDD simulations. We discuss the regimes in which GP-DDD is able to adequately capture the variation of the flow stress with strain rate in the single slip loading condition. In conclusion, a simulation using GP-DDD requires ~40 times fewer degrees of freedom for a copper single slip loading case, thus reducing computational time and complexity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Unveiling enhanced oxidation resistance and mechanical integrity of multicomponent ultra–high temperature carbides

The development of a new class of multicomponent ultra-high temperature ceramics (MC-UHTCs), often referred to as high-entropy UHTCs, has gained increased interest due to the possibility of improved thermomechanical and oxidation properties. In this study, a systematic approach by gradual addition in the UHTC components ranging from a binary to a dense quaternary (Ta,Nb,Hf,Ti)C is synthesized using spark plasma sintering (SPS). The solid solutioning was the critical factor in homogenizing the composition in the multicomponent system. The segregation of NbC and HfC was seen in binary and ternary UHTC systems, while a single-phase homogeneity was observed in the quaternary UHTC improving its hardness up to 34.8 GPa. The presence of closely spaced slip lines in the MC-UHTCs enhances resistance to indentation damage up to 72% at an applied load of 200 N. The formation of complex mixed oxide phase of Hf6Ta2O17 ensued in the lower to negligible oxidation even up to 3 min of plasma exposure with temperature exceeding 2800°C. In sum, though the entropy remains medium (0.96R) for the selected system, the quaternary UHTC system undoubtedly has significantly better thermomechanical performance when compared to established baseline UHTCs. Furthermore, this raises the debate on the justification for calling a multicomponent system a “high entropy” to be seen in a new light. The developed MC-UHTCs elicits the paradigm of this new class of UHTCs expanding their potential in thermal protection systems for hypersonic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

COMPILE: a GWAS computational pipeline for gene discovery in complex genomes

Abstract Background Genome-Wide Association Studies (GWAS) are used to identify genes and alleles that contribute to quantitative traits in large and genetically diverse populations. However, traits with complex genetic architectures create an enormous computational load for discovery of candidate genes with acceptable statistical certainty. We developed a streamlined computational pipeline for GWAS (COMPILE) to accelerate identification and annotation of candidate maize genes associated with a quantitative trait, and then matches maize genes to their closest rice and Arabidopsis homologs by sequence similarity. Results COMPILE executed GWAS using a Mixed Linear Model that incorporated, without compression, recent advancements in population structure control, then linked significant Quantitative Trait Loci (QTL) to candidate genes and RNA regulatory elements contained in any genome. COMPILE was validated using published data to identify QTL associated with the traits of α-tocopherol biosynthesis and flowering time, and identified published candidate genes as well as additional genes and non-coding RNAs. We then applied COMPILE to 274 genotypes of the maize Goodman Association Panel to identify candidate loci contributing to resistance of maize stems to penetration by larvae of the European Corn Borer ( Ostrinia nubilalis ). Candidate genes included those that encode a gene of unknown function, WRKY and MYB-like transcriptional factors, receptor-kinase signaling, riboflavin synthesis, nucleotide-sugar interconversion, and prolyl hydroxylation. Expression of the gene of unknown function has been associated with pathogen stress in maize and in rice homologs closest in sequence identity. Conclusions The relative speed of data analysis using COMPILE allowed comparison of population size and compression. Limitations in population size and diversity are major constraints for a trait and are not overcome by increasing marker density. COMPILE is customizable and is readily adaptable for application to species with robust genomic and proteome databases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Load Forecasting in Electric Utility Integrated Resource Planning

Integrated resource planning (IRP) is a process used by many vertically-integrated U.S. electric utilities to determine least-cost/risk supply and demand-side resources that meet government policy objectives and future obligations to customers and, in many cases, shareholders. Forecasts of energy and peak demand are a critical component of the IRP process. There have been few, if any, quantitative studies of IRP long-run (planning horizons of two decades) load forecast performance and its relationship to resource planning and actual procurement decisions. In this paper, we evaluate load forecasting methods, assumptions, and outcomes for 12 Western U.S. utilities by examining and comparing plans filed in the early 2000s against recent plans, up to year 2014. We find a convergence in the methods and data sources used. We also find that forecasts in more recent IRPs generally took account of new information, but that there continued to be a systematic over-estimation of load growth rates during the period studied. We compare planned and procured resource expansion against customer load and year-to-year load growth rates, but do not find a direct relationship. Load sensitivities performed in resource plans do not appear to be related to later procurement strategies even in the presence of large forecast errors. These findings suggest that resource procurement decisions may be driven by other factors than customer load growth. Our results have important implications for the integrated resource planning process, namely that load forecast accuracy may not be as important for resource procurement as is generally believed, that load forecast sensitivities could be used to improve the procurement process, and that management of load uncertainty should be prioritized over more complex forecasting techniques.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗