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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Energy Management Information System Powers NREL's Intelligent Campus

NREL's Intelligent Campus program leverages its own laboratory buildings as research instruments to study renewable energy, energy efficiency, and energy storage, integration, and analysis with real, quantitative measurements. At the heart of NREL's Intelligent Campus program is its Energy Management Information System (EMIS), a family of tools and services used to manage building and campus energy use. NREL's EMIS includes capabilities, such as benchmarking and monthly utility tracking, interval meter analytics, equipment fault detection and diagnostics, condition-based monitoring, and supervisory control, enabling unprecedented energy management capabilities. The system serves as a demonstration project for other federal facilities interested in learning about its design, features, and benefits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Energy Management Information System Powers NREL's Intelligent Campus

EMIS↗

DOE OSTI2021

Distributed, Intelligent Edge-Sensing for a Smarter Grid

The electric grid is undergoing major transformations and developments resulting in unprecedented levels of volatility, uncertainty, and stress on grid infrastructure. Smart sensors and methods aiding in advanced visibility and situational awareness are key for tackling these issues. In this work, a decentralized architecture is proposed, where sensing, local computation and control capability are embedded in the edge devices, communicating with a set of trusted 'data mules' in a 'delay-tolerant' manner, while functioning autonomously. This system has been designed and implemented as an overall platform – called Global Asset Monitoring, Management and Analytics (GAMMA) Platform intended to provide the backbone for a global array of sensors and actuators. Further, as a building block for advanced current sensing solutions, a smart, low-cost ‘clip-on’ current sensor based on PCB-embedded Rogowski coil has been developed. The sensor hosts a novel signal conditioning stage allowing an 'auto-tuning' feature, resulting in a universal current sensor design for measuring a wide range of currents, including faults for smart grid applications. Finally, the research proposes a method to instrument and monitor key parameters for the most common electric utility asset – the pole-top distribution transformer. The work done in this research enables scalable, edge-intelligent sensing solutions for monitoring grid infrastructure, allowing utility operators to gain advanced visibility in an economical way.

Kulkarni, Shreyas Bhalchandra↗

DOE OSTI2021

Reduced scaling formulation of CASPT2 analytical gradients using the supporting subspace method

We present a reduced scaling and exact reformulation of state specific complete active space second-order perturbation (CASPT2) analytical gradients in terms of the MP2 and Fock derivatives using the supporting subspace method. This work follows naturally from the supporting subspace formulation of the CASPT2 energy in terms of the MP2 energy using dressed orbitals and Fock builds. For a given active space configuration, the terms corresponding to the MP2-gradient can be evaluated with O(N5) operations, while the rest of the calculations can be computed with O(N3) operations using Fock builds, Fock gradients, and linear algebra. When tensor-hyper-contraction is applied simultaneously, the computational cost can be further reduced to O(N4) for a fixed active space size. The new formulation enables efficient implementation of CASPT2 analytical gradients by leveraging the existing graphical processing unit (GPU)-based MP2 and Fock routines. We present benchmark results that demonstrate the accuracy and performance of the new method. Example applications of the new method in ab initio molecular dynamics simulation and constrained geometry optimization are given.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1978

Dynamics of the quiescent solar corona

An analytical model for the quiescent inhomogeneous solar corona is developed on the basis of the hypothesis that looplike structures are the basic coronal building blocks. By assuming that quiescent loop structures observed in X-rays are in hydrostatic equilibrium, it is demonstrated that such loops must have their temperature maximum located near their apex and that substantial nonradiative energy deposition must occur along most of their length. The calculations yield a unique relation among loop temperature, pressure, and size, which fits the X-ray observations of quiescent structures well and is consistent with the initial assumption of hydrostatic equilibrium. The results suggest that the coronal loops visible in X-rays represent a relatively steady-state equilibrium of the confined plasmas and that fluctuations in such quantities as the local heating rate can lead to dynamically unstable states in which the loop plasma does not attain a temperature sufficient for X-ray emission. A parameterization of various proposed coronal heating theories is also developed within the context of the analytical model.

Rosner, R.↗

DOE OSTI2026

Idealized Offshore Low‐Level Jets for Turbine Structural Impact Considerations

Low-level jets (LLJs) describe conditions in which the wind speed reaches a local maximum with respect to altitude near the surface; they have been observed intermittently in the US mid-Atlantic offshore environment. LLJs pose unique operating conditions for future wind turbines operating in the region, such as negative shear and locally strong veer, but they are not typically considered in existing turbine standards. This work builds upon recent research that explains the formation and evolution of the US mid-Atlantic LLJs through a simple analytical governing equation. We generate several LLJ inflow conditions with varying jet characteristics based on this analytical model and create monotonically sheared (MS) analogues with matched veer to assess the impacts of the LLJ on turbine performance and loading. Using aeroelastic simulations with these inflow conditions on the International Energy Agency 15-MW reference turbine, we find that the LLJ leads to a greater range of tower-top pitching and yawing moments, which could contribute to larger accumulated structural fatigue in components compared to MS inflow. These preliminary results demonstrate a path toward a unified set of test cases for low-level wind maxima that can inform the International Electrotechnical Commission standards related to offshore wind turbine design.

17 WIND ENERGY↗

DOE OSTI2024

Comparison of reduced model predictions for divertor detachment onset and reattachment timescales in ASDEX Upgrade and JET experiments

Building on prior analysis of ASDEX Upgrade (AUG) experiments (Henderson et al 2023 Nucl. Fusion63 086024), this study compares simple analytical formula predictions for divertor detachment onset and reattachment timescales in JET experiments. Detachment onset primarily scales with divertor neutral pressure, impurity concentration, power directed to the targets, machine size, and integral perpendicular power decay length. JET experiments, focusing on seeding mixtures of Ne and Ar, align with the detachment onset predictions. Radiation efficiencies among the impurities show good agreement with the model predictions, contrasting with AUG observations which suggested higher efficiency for Ar and lower efficiency for Ne. The time taken to re-ionise the neutral volume in front of the outer target in fully detached divertor conditions was measured following both abrupt increases in injected neutral beam power and, separately, cutting of the impurity gas flow. Re-ionisation of the neutrals occurs within approximately 1 s on JET, which aligns with the simple model prediction derived from AUG data. While the AUG results are not new, their comparison with the JET results enhances understanding, reinforcing confidence in using simple models to predict future reactor scenarios.

JET↗

DOE OSTI2023

Accelerated Materials Design for Molten Salt Technologies Using Innovative High-Throughput Methods

The focus of the project is on building an innovative accelerated materials design platform for molten salt technologies using novel high-throughput methods coupled to data analytics. The main objectives is to predict a FeCrMnNi alloy compositional space with better corrosion resistance than stainless steel 316 and identify new molten salt corrosion mechanisms. The project demonstrates the feasibility to use high-throughput methods coupled to data analytics to accelerate alloy design for extreme environments applications. Using a trained and tested machine learning (ML) model, 2000 FeCrMnNi alloy corrosion rate in molten chloride salts were predicted and a compositional field with corrosion rate lower than 316 stainless steel was identified. The ML model interpretability unveiled multiple features of importance in the model prediction. Some features were expected to be of relative significance, such as work function, surface energy and alloy electronegativity, and the ML model interpretability analysis confirmed those. On the other hand, the most important feature is the diffusion coefficient of Ni in the bulk alloy which indicates that a surface diffusion mechanism plays an important role in the overall corrosion mechanism in molten salts.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Targeted Quantification of Protein Phosphorylation and Its Contributions towards Mathematical Modeling of Signaling Pathways

Post-translational modifications (PTMs) are key regulatory mechanisms that can control protein function. Of these, phosphorylation is the most common and widely studied. Because of its importance in regulating cell signaling, precise and accurate measurements of protein phosphorylation across wide dynamic ranges are crucial to understanding how signaling pathways function. Although immunological assays are commonly used to detect phosphoproteins, their lack of sensitivity, specificity, and selectivity often make them unreliable for quantitative measurements of complex biological samples. Recent advances in Mass Spectrometry (MS)-based targeted proteomics have made it a more useful approach than immunoassays for studying the dynamics of protein phosphorylation. Selected reaction monitoring (SRM)—also known as multiple reaction monitoring (MRM)—and parallel reaction monitoring (PRM) can quantify relative and absolute abundances of protein phosphorylation in multiplexed fashions targeting specific pathways. In addition, the refinement of these tools by enrichment and fractionation strategies has improved measurement of phosphorylation of low-abundance proteins. The quantitative data generated are particularly useful for building and parameterizing mathematical models of complex phospho-signaling pathways. Potentially, these models can provide a framework for linking analytical measurements of clinical samples to better diagnosis and treatment of disease.

mathematical modeling↗

NASA NTRS1980

SPS antenna element evaluation

The SPS transmitting array requires an architecture which will provide a low weight, high efficiency and high structural rigidity. Waveguide slot arrays constitute the most desirable option. Consequently, such an array was chosen for the SPS. Waveguide slot arrays offer high efficiency, uniform illumination, and are fairly lightweight. Bandwidths of such arrays are narrow, typically 1/2-2%. Although this does not directly impact the SPS, which transmits power at a single frequency of 2.45 GHz, the narrow bandwidth does constrain the thermal and mechanical tolerances of the antenna. The purpose of this program is to better define the electronic aspects of an SPS specific waveguide slot array. The specific aims of the program are as follows: (1) To build a full-scale half-module, 10 stick, array, the design parameters for which are to be determined analytical considerations tempered by experimental data on a single slotted radiating stick, (2) To experimentally evaluate the completed array with respect to antenna pattern, impedance and return loss; and (3) To measure swept transmission amplitude and phase to provide a data base for design of a receiving antenna.

Lunden, C. D.↗

NASA NTRS1991

Evaluation of Fungal Metabolic Compounds Released to the Air in a Restricted Environment

The metabolic action of selected fungi species on common components of the interior of Space Station Freedom (SSF) will be tested. When present, volatile organic chemicals will be collected on porous polymer adsorbent columns. Using thermal desorption, the volatile compounds will be passed onto a gas chromatographic column for analysis. The Space Station Freedom (SSF) modular complex will largely be individually self contained and the established air environment will not be easily adjusted. The development and maintenance of a safe working environment offers a considerable challenge. Present plans for use of SSF acknowledge periods of manned activities and alternate times when the station is unmanned. The obvious necessity for clean and safe air and water during periods of use have been pursued as fundamental systems to SSF success. Somewhat less obvious, although perhaps of no less importance to the success of long term cyclic usage, are those periods of inactivity. It is during these periods when spores from microorganisms may be afforded the best conditions to germinate and in the vegetative form react with the complex synthetic chemical polymers which compose the furnishings and hardware of SSF nodes. Biodegradation could constitute a real hygiene problem, if the organisms form and release volatile organic chemicals. Similar problems have been documented in closed and improperly ventilated buildings and work spaces. Many of the metabolic products of fungi and bacterial growth create a variety of health problems. Analytical chemical techniques will first be used to document the growth of Aspergillus, Penicillium, and Cladosporium fungal species on the potential substrates Nomex and Kevlar. Any volatile organics that are released will be measured using the spectrum of gas adsorption chromatography. The level of microbial contamination that is necessary to produce such volatile compounds and the relative amounts expected to accumulate will be estimated.

Ferebee, Robert N.↗

NASA NTRS2009

Development of an On-board Failure Diagnostics and Prognostics System for Solid Rocket Booster

We develop a case breach model for the on-board fault diagnostics and prognostics system for subscale solid-rocket boosters (SRBs). The model development was motivated by recent ground firing tests, in which a deviation of measured time-traces from the predicted time-series was observed. A modified model takes into account the nozzle ablation, including the effect of roughness of the nozzle surface, the geometry of the fault, and erosion and burning of the walls of the hole in the metal case. The derived low-dimensional performance model (LDPM) of the fault can reproduce the observed time-series data very well. To verify the performance of the LDPM we build a FLUENT model of the case breach fault and demonstrate a good agreement between theoretical predictions based on the analytical solution of the model equations and the results of the FLUENT simulations. We then incorporate the derived LDPM into an inferential Bayesian framework and verify performance of the Bayesian algorithm for the diagnostics and prognostics of the case breach fault. It is shown that the obtained LDPM allows one to track parameters of the SRB during the flight in real time, to diagnose case breach fault, and to predict its values in the future. The application of the method to fault diagnostics and prognostics (FD&P) of other SRB faults modes is discussed.

Smelyanskiy, Vadim N.↗

DOE OSTI2021

xSDK: Building an ecosystem of highly efficient math libraries for exascale

Current efforts to build increasingly powerful computer architectures are opening up new avenues for more complex and higher fidelity simulations coupled with data analytics and learning, leading to new scientific insights and deeper understanding. At one extreme, exascale computers will be much faster than previous computer generations (performing 10 18 operations per second—that is, 1,000 times faster than petascale). To achieve these performance improvements, computer architectures are becoming increasingly complex, with deep memory hierarchies, very high node and core counts, and heterogeneous features such as graphics processing units (GPUs). Such architectural changes impact the full breadth of computing scales, as heterogeneity pervades even current-generation laptops, workstations, and moderate-sized clusters. While emerging advanced architectures provide unprecedented opportunities, they also present significant challenges for developers of scientific applications, such as multiphysics and multiscale codes, who must adapt their software to handle disruptive changes in architectures and new programming models that have not yet stabilized. Developers must consider increasing concurrency while reducing communication and synchronization, and other complexities such as the potential for using mixed precision to leverage the compute power available in low-precision tensor cores. On one hand, developers must implement new scientific capabilities, which in turn increase code complexity. On the other hand, the codes must be ported to new architectures, requiring the inclusion of new programming models and the restructuring of code to achieve good performance. Addressing these issues is beyond the capability of any single person or team—leading to the need for collaboration among many teams, who encapsulate their expertise in reusable software and work together to create sustainable software ecosystems.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1990

Structural evaluation of composite fuselage structure fabricated using a THERM-X process

An experimental and analytical program has been implemented to evaluate the structural performance of complex composite parts made using THERM-X processing techniques. Preliminary analysis shows 22-percent cost savings for parts made with a THERM-X process over parts made with conventional manufacturing methods. Results of building-block tests from the coupon to the element level, which represent structural details of the curved integrally stiffened panel selected as the full-scale article, are also reported. Comparisons with baseline results and analytical predictions show that THERM-X processing yields parts with stiffness and strength comparable to or slightly better than conventional manufacturing procedures. Compression strength after low-speed impact damage (caused by a drop weight impactor) is also comparable to parts fabricated with conventional methods.

Kassapoglou, Christos↗

NASA NTRS2005

Utilization of the Building-Block Approach in Structural Mechanics Research

In the last 20 years NASA has worked in collaboration with industry to develop enabling technologies needed to make aircraft safer and more affordable, extend their lifetime, improve their reliability, better understand their behavior, and reduce their weight. To support these efforts, research programs starting with ideas and culminating in full-scale structural testing were conducted at the NASA Langley Research Center. Each program contained development efforts that (a) started with selecting the material system and manufacturing approach; (b) moved on to experimentation and analysis of small samples to characterize the system and quantify behavior in the presence of defects like damage and imperfections; (c) progressed on to examining larger structures to examine buckling behavior, combined loadings, and built-up structures; and (d) finally moved to complicated subcomponents and full-scale components. Each step along the way was supported by detailed analysis, including tool development, to prove that the behavior of these structures was well-understood and predictable. This approach for developing technology became known as the "building-block" approach. In the Advanced Composites Technology Program and the High Speed Research Program the building-block approach was used to develop a true understanding of the response of the structures involved through experimentation and analysis. The philosophy that if the structural response couldn't be accurately predicted, it wasn't really understood, was critical to the progression of these programs. To this end, analytical techniques including closed-form and finite elements were employed and experimentation used to verify assumptions at each step along the way. This paper presents a discussion of the utilization of the building-block approach described previously in structural mechanics research and development programs at NASA Langley Research Center. Specific examples that illustrate the use of this approach are included from recent research and development programs for both subsonic and supersonic transports.

Rouse, Marshall↗

DOE OSTI2023

Automated instant labeling chemistry workflow for real-time monitoring of monoclonal antibody N -glycosylation

With the transition toward continuous bioprocessing, process analytical technology (PAT) is becoming necessary for rapid and reliable in-process monitoring during biotherapeutics manufacturing. Bioprocess 4.0 is looking to build end-to-end bioprocesses that include PAT-enabled real-time process control. This is especially important for drug product quality attributes that can change during bioprocessing, such as protein N-glycosylation, a critical quality attribute for most monoclonal antibody (mAb) therapeutics. Glycosylation of mAbs is known to influence their efficacy as therapeutics and is regulated for a majority of mAb products on the market today. Currently, there is no method to truly measure N-glycosylation using on-line PAT, hence making it impractical to design upstream process control strategies. We recently described the N-GLYcanyzer workflow: an integrated PAT unit that measures mAb N-glycosylation within 3 hours of automated sampling from a bioreactor. Here, we integrated Agilent's Instant Procainamide (InstantPC) based chemistry workflow into the N-GLYcanyzer PAT unit to allow for nearly 10× faster near real-time analysis of mAb glycoforms. Furthermore, our methodology is explained in detail to allow for replication of the PAT workflow as well as present a case study demonstrating the use of this PAT to autonomously monitor a mammalian cell perfusion process at the bench scale to gain increased knowledge of mAb glycosylation dynamics during continuous biologics manufacturing using Chinese hamster ovary (CHO) cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

ICAT: The Interactive Corpus Analysis Tool

The Interactive Corpus Analysis Tool (ICAT) is a Python library for creating dashboards to explore textual datasets and build simple binary classification models to help filter through them and focus on entries of interest. This tool uses a form of interactive machine learning (IML), a paradigm of “machine teaching” (Simard et al., 2017) that sits at the intersection of the fields of human computer interaction (HCI), visual analytics, and machine learning. The intent of ICAT is to allow subject matter experts (SME) with limited to no experience in machine learning to benefit from an iterative human-in-the-loop (HITL) approach to building their own model without needing to understand the details of the underlying algorithm. This interactivity is achieved by allowing the user to create features, label data points, and visually manipulate a representation of the features to manually cluster and investigate data, while a model is trained on the fly based on these actions. ICAT is built on top of the Panel (Holoviz, 2018) library, using a combination of Vega, a custom IPyWidget using D3, and ipyvuetify, and is intended to be used inside of a Jupyter environment.

Martindale, Nathan [Oak Ridge National Laboratory ↗

DOE OSTI2024

Navigating Exascale Operational Data Analytics: From Inundation to Insight

In this paper, we address the challenges in achieving sustainable data-driven efficiency by providing a detailed exploration of the end-to-end operational data analytics (ODA) framework that evolved through two generations of supercomputer systems at the Oak Ridge Leadership Computing Facility (OLCF). This framework addresses large data streams ingested from heavily instrumented HPC environment that accumulates multi-terabytes per day. We outline the multifaceted data life cycle across HPC procurement, operations, and research & development, identifying key obstacles and design decisions that shape effective strategies in building and supporting data pipelines end-to-end. By sharing key insights and lessons learned from our experience, we offer recommendations for the HPC community on enabling sustainable operational data analytics and beyond. Our contributions aim to bridge the gap between potential and real benefits of operational data, guiding future efforts towards integrated and sustainable operational intelligence in high-performance computing environments.

Shin, Woong↗