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DOE OSTI2023

IDAES-PSE 2.1.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.1.0 Release Highlights New IDAES Examples Repository Starting with this release, the IDAES examples are developed in the new IDAES/examples repository. Along with many content and usability improvements, the most significant changes are: To install the examples, after installing IDAES, run pip install idaes-examples The idaes get-examples command, previously used for this, has been removed The HTML version is now available at https://idaes-examples.readthedocs.io The previous URL, https://idaes.github.io/examples-pse, will not be updated and may be removed at some point in the future For more details, refer to the resources available at IDAES/examples. Removal of Non-Functional Apps A review of the code in the idaes/apps and idaes/models_extra folders was undertaken, and a number of tools were identified as being outdated or non-functional and no longer supported by their development teams. Due to this, the following tools have been removed: idaes/apps/alamopy_depr (note that the new ALAMOpy interface remains avaialble in idaes/core/surrogates) idaes/apps/helmet idaes/apps/ripe idaes/apps/roundingRegression idaes/models_extra/carbon_capture Pyomo 6.6 This version of IDAES is the first requiring Pyomo 6.6. This version of Pyomo contains multiple internal improvements and refactorings. While for the majority of cases this should have positive or no impact on solvability of IDAES models, we are aware of a small number of models that have been affected as a result of these changes. For more information, refer to the Pyomo 6.6.1 release notes. Other highlights Model Initialization A prototype API for a new approach to initializing IDAES models is now available which makes available some new techniques for initializing models. This is documented in the Initializing Models Reference Guide Modular Properties Framework Support for some transport properties Helmholtz Equation of State properties Better error checking for case where unit models are set to include phase equilibrium but the property package is set to support only a single phase Multi-Stream Contactor model: a new base model for systems involving contacting of two or more streams with mass transfer. This model is intended to be used as the foundation for models such as membrane separators, solvent extraction and other similar processes. This is documented in the Multi-Stream Contactor Reference Guide idaes/models_extra/power_generation report() methods for unit models using Helmholtz equation of state General Code Maintenance Streamlining of dependencies and creation of new optional dependency groupings to support non-core tools General linting of codebase to ensure compliance with most pylint checks Spell checking of all code and doc strings Removal of backward compatibility code for Python 2

IDAES↗

NASA NTRS1971

Global trajectory targeting via computer graphics

A technique is described in which the two-point boundary value problem (TPBVP) may be solved with the aid of interactive computer graphics. The particular TPBVP considered is the optimal electric propulsion space trajectory problem. An appropriate two-dimensional projection of the TPBVP mapping, or trajectory, is displayed on the computer's television screen, and a man-in-the-loop varies selected trajectory starting conditions in the fashion of a nonlinear walk until the viewed trajectory endpoint lies near a displayed target. Once global targeting is accomplished in this manner, program internal logic can easily handle local targeting to strongly solve the TPBVP.

Mann, F. I.↗

NASA NTRS2012

Wall Pressure Unsteadiness and Side Loads in Overexpanded Rocket Nozzles

Surveys of both the static and dynamic wall pressure signatures on the interior surface of a sub-scale, cold-flow and thrust optimized parabolic nozzle are conducted during fixed nozzle pressure ratios corresponding to FSS and RSS states. The motive is to develop a better understanding for the sources of off-axis loads during the transient start-up of overexpanded rocket nozzles. During FSS state, pressure spectra reveal frequency content resembling SWTBLI. Presumably, when the internal flow is in RSS state, separation bubbles are trapped by shocks and expansion waves; interactions between the separated flow regions and the waves produce asymmetric pressure distributions. An analysis of the azimuthal modes reveals how the breathing mode encompasses most of the resolved energy and that the side load inducing mode is coherent with the response moment measured by strain gauges mounted upstream of the nozzle on a flexible tube. Finally, the unsteady pressure is locally more energetic during RSS, albeit direct measurements of the response moments indicate higher side load activity when in FSS state. It is postulated that these discrepancies are attributed to cancellation effects between annular separation bubbles.

Baars, Woutijn J.↗

NASA NTRS2014

Growth of CdZnTe Crystals for Radiation Detector Applications by Directional Solidification

Advances in Cadmium Zinc Telluride (Cd(sub 1-x)Zn(sub x)Te) growth techniques are needed for the production of large-scale arrays of gamma and x-ray astronomy. The research objective is to develop crystal growth recipes and techniques to obtain large, high quality CdZnTe single crystal with reduced defects, such as charge trapping, twinning, and tellurium precipitates, which degrade the performance of CdZnTe and, at the same time, to increase the yield of usable material from the CdZnTe ingot. A low gravity material experiment, "Crystal Growth of Ternary Compound Semiconductors in Low Gravity Environment", will be performed in the Material Science Research Rack (MSRR) on International Space Station (ISS). One section of the flight experiment is the melt growth of CdZnTe ternary compounds. This talk will focus on the ground-based studies on the growth of Cd(sub 0.80)Zn(sub 0.20)Te crystals for radiation detector applications by directional solidification. In this investigation, we have improved the properties that are most critical for the detector applications (electrical properties and crystalline quality): a) Electrical resistivity: use high purity starting materials (with reproducible impurity levels) and controlled Cd over pressure during growth to reproducibly balance the impurity levels and Cd vacancy concentration b) Crystalline quality: use ultra-clean growth ampoule (no wetting after growth), optimized thermal profile and ampoule design, as well as a technique for supercool reduction to growth large single crystal with high crystalline quality

Su, Ching-Hua↗

NASA NTRS2017

Aeroelastic Modeling of X-56A Stiff-Wing Configuration Flight Test Data

Aeroelastic stability and control derivatives for the X-56A Multi-Utility Technology Testbed (MUTT), in the stiff-wing configuration, were estimated from flight test data using the output-error method. Practical aspects of the analysis are discussed. The orthogonal phase-optimized multisine inputs provided excellent data information for aeroelastic modeling. Consistent parameter estimates were determined using output error in both the frequency and time domains. The frequency domain analysis converged faster and was less sensitive to starting values for the model parameters, which was useful for determining the aeroelastic model structure and obtaining starting values for the time domain analysis. Including a modal description of the structure from a finite element model reduced the complexity of the estimation problem and improved the modeling results. Effects of reducing the model order on the short period stability and control derivatives were investigated.

Grauer, Jared A.↗

DOE OSTI2024

Stochastic Approximation for Multi-period Simulation Optimization with Streaming Input Data

We consider a continuous-valued simulation optimization (SO) problem, where a simulator is built to optimize an expected performance measure of a real-world system while parameters of the simulator are estimated from streaming data collected periodically from the system. At each period, a new batch of data is combined with the cumulative data and the parameters are re-estimated with higher precision. The system requires the decision variable to be selected in all periods. Therefore, it is sensible for the decision-maker to update the decision variable at each period by solving a more precise SO problem with the updated parameter estimate to reduce the performance loss with respect to the target system. We define this decision-making process as the multi-period SO problem and introduce a multi-period stochastic approximation (SA) framework that generates a sequence of solutions. Two algorithms are proposed: Re-start SA (ReSA) reinitializes the stepsize sequence in each period, whereas Warm-start SA (WaSA) carefully tunes the stepsizes, taking both fewer and shorter gradient-descent steps in later periods as parameter estimates become increasingly more precise. We show that under suitable strong convexity and regularity conditions, ReSA and WaSA achieve the best possible convergence rate in expected sub-optimality either when an unbiased or a simultaneous perturbation gradient estimator is employed, while WaSA accrues significantly lower computational cost as the number of periods increases. In addition, we present the regularized ReSA, which obviates the need to know the strong convexity constant and achieves the same convergence rate at the expense of additional computation.

Computer Science↗

DOE OSTI2022

Design and optimization of supersonic turbines for detonation combustors

Detonation-based engines offer a potential surge in efficiency for compact thermal power systems. However, these cycles require ad-hoc components adapted to the high outlet velocity from the detonation combustors. This paper presents the design methodology of turbine stages suitable for supersonic inlet conditions and provides a detailed analysis of optimized turbine geometries. A reduced-order solver examines the supersonic blade rows’ functional design space, quantifies the turbine’s non-isentropic performance, and budgets the turbine loss for different optimized leading-edge designs and chord to pitch ratios. The shock-wave interactions were identified as the predominant contributor to turbine losses, and optimal pitch-chord ratios were determined for various inlet Mach numbers. Finally, with this tool, the specific-power output for a wide range of design configurations was computed; and the metal angle that ensures flow starting and maximizes power extraction was calculated. The detailed numerical study describes the flow interactions in a supersonic turbine and offers new correlations to guide the design of future supersonic turbines.

42 ENGINEERING↗

DOE OSTI2023

HB650 Cryomodule Design: From Prototype to Production

In early 2023 the assembly of the prototype HB650 cryomodule (pHB650 CM) was completed and cold tests started to evaluate its performance. The lessons learned from the design, assembly and preliminary cold tests of this cryomodule, and from the design of the SSR2 pre-production cryomodule played a fundamental role during the design optimization process of the production HB650 cryomodule (HB650 CM). Several workshops have been organized to share experiences and solve problems. This paper presents the main design changes from pHB650 to the HB650 production cryomodules and their impact on the heat loads.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Distributed Wind Controls: A Research Roadmap for Microgrids, Infrastructure Resilience, and Controls Launchpad (MIRACL)

The Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project’s controls research area aims to expand the benefits from distributed wind (DW) generation assets beyond solely providing low cost power directly to consumers. To make distributed wind turbines operate more effectively there is a need for more advanced ways to control them, allowing power companies, businesses, and energy consumers to take advantage of the unique characteristics of wind energy. DW can contribute to the safe and secure operation of grid by providing services such as voltage regulation, frequency regulation, spinning reserves, and even black start capabilities. In the larger DER context where much of the research has focused around solar technologies, the inertia available in wind technologies has generally not been considered. For wind turbines to provide these services in an optimal and expanded way, development and demonstration of control methods and communication interfaces within a grid and microgrid framework are required. In this document, NREL led the literature review in collaboration with SNL, of DER controls-focused integration research to establish a baseline for the controls research under the MIRACL project to identify specific control functions to be focused on throughout this project. This literature review focused primarily on the control functions of variable distributed generation, largely pulling from past solar PV and battery controls works, with a specific focus on applicability for distributed wind energy systems. The goal of this document is to identify a research roadmap based on the open literature and past national laboratory works to inform advanced wind turbine and power electronics control functions for four use cases: 1) distributed wind in isolated systems, 2) grid-connected microgrids (wind-hybrid systems and islanded operation), 3) behind-the-meter distributed wind applications in the power distribution systems, and 4) front-of-the-meter distributed wind applications in the power distribution systems.

17 WIND ENERGY↗

NASA NTRS1977

Microwave multispectral investigations of snow

A long term observational program on microwave emission and scatter behavior under controlled conditions, was started at a high altitude alpine test site. All stages of development of snow cover during the whole season are under investigation. The study was done to achieve required knowledge on microwave radiative properties of snow for optimization of the microwave payloads of air and spaceborne snow sensors and for the interpretation of large scale snow maps obtained by these sensors. Preliminary results of the first month obtained with radiometers at 4.9, 10.5, 21 and 36 GHz are presented.

Schanda, E.↗

NASA NTRS1989

Fuel-optimal trajectories of aeroassisted orbital transfer with plane change

The problem of minimization of fuel consumption during the atmospheric portion of an aeroassisted, orbital transfer with plane change is addressed. The complete mission has required three characteristic velocities, a deorbit impulse at high earth orbit (HEO), a boost impulse at the atmospheric exit, and a reorbit impulse at low earth orbit (LEO). A performance index has been formulated as the sum of these three impulses. Application of optimal control principles has led to a nonlinear, two-point, boundary value problem which was solved by using a multiple shooting algorithm. The strategy for the atmospheric portion of the minimum-fuel transfer is to start initially with the maximum positive lift in order to recover from the downward plunge, and then to fly with a gradually decreasing lift such that the vehicle skips out of the atmosphere with a flight path angle near zero degrees.

Naidu, Desineni Subbaramaiah↗

NASA NTRS1989

Fuel-optimal trajectories of aeroassisted orbital transfer with plane change

Naidu, D. S.↗

NASA NTRS1999

Investigation of the Influence of Microgravity on Transport Mechanism in a Virtual Spaceflight Chamber: A Flight Definition Program

A need exists for understanding precisely how particles move and interact in a fluid in the absence of gravity. Such understanding is required, for example, for modeling and predicting crystal growth in space where crystals grow from solution around nucleation sites as well as for any study of particles or bubbles in liquids or in experiments where particles are used as tracers for mapping microconvection. We have produced an exact solution to the general equation of motion of particles at extremely low Reynolds number in microgravity that covers a wide range of interesting conditions. We have also developed diagnostic tools and experimental techniques to test the validity of the general equation . This program, which started in May, 1998, will produce the flight definition for an experiment in a microgravity environment of space to validate the theoretical model. We will design an experiment with the help of the theoretical model that is optimized for testing the model, measuring g, g-jitter, and other microgravity phenomena. This paper describes the goals, rational, and approach for the flight definition program. The first objective of this research is to understand the physics of particle interactions with fluids and other particles in low Reynolds number flows in microgravity. Secondary objectives are to (1) observe and quantify g-jitter effects and microconvection on particles in fluids, (2) validate an exact solution to the general equation of motion of a particle in a fluid, and (3) to characterize the ability of isolation tables to isolate experiments containing particle in liquids. The objectives will be achieved by recording a large number of holograms of particle fields in microgravity under controlled conditions, extracting the precise three-dimensional position of all of the particles as a function of time and examining the effects of all parameters on the motion of the particles. The feasibility for achieving these results has already been established in the ongoing ground-based NRA, which led to the "virtual spaceflight chamber" concept.

Trolinger, James D.↗

NASA NTRS2018

Information Theory Applied to Decision Making Structures

Decision making structures, such as control boards, process information on many topics as they select options for the system and project. The decisions are based on the information known to the board members and presenters (subject matter experts) and shared at the board during discussion. This information flow through this process can be modelled using information theory. Information theory provides a mathematical basis to understand the flow of information through the decision making process and the information needed for a particular decision. Information theory also provides the mathematical relationships on which to base the optimal decision making structure for a specific system development and organizational structure. Since decision making bodies provide control for the system or project, control theory can be used to construct a decision making model. This provides a starting point for adding cognitive science models. Information processing by each individual board participant can be represented through cognitive processes which are integrated across the board participants through information theory relationship. The set theory view of information theory provides a structure in which to look at the relationships between the participants in a decision making structure.

Watson, Michael D.↗

NASA NTRS2018

Information Theory Applied to Decision Making Structures

Watson, Michael D.↗

DOE OSTI2023

Solid oxide metal-air redox batteries (SOMARB)

The solid oxide metal-air redox batteries (SOMARB), composed of reversible solid oxide fuel cell (RSOFC) and energy storage unit (ESU), is an emerging technology for large-scale energy storage owing to its advantages in high energy density, high rate capability, decoupled energy and power components, all solid state structure, high safety and scalability. Starting with introducing the working principle of this battery, thermodynamics and kinetics, and battery chemistries based on Fe, Mo, and Wo of SOMARB are illustrated. The strategies to improve the performance of Fe-based SOMARB via optimizing RSOFC and ESU are discussed in detail. Finally, several high temperature metal-air batteries derived from SOMARB are introduced. The comparison with other batteries shows that SOMARB is expected to play an important role in future grid and renewable energy storage with concurrent advances in SOFC stack and system design.

Zhang, Cuijuan↗

DOE OSTI2025

A Route to Design Novel Functional Peptides by Applying a Denoising Diffusional Model to mRNA Display Libraries

In vitro directed evolution techniques, such as mRNA display, enable peptide ligand discovery and optimization. However, physical libraries that rely on a genetic code can only search a small fraction of sequence space due to inherent biases in the genetic code and experimental limitations. To address this challenge, denoising diffusion implicit models (DDIMs) are applied to generate novel peptide ligands against B‐cell lymphoma extra‐large (Bcl‐x L ), a key cancer target. Starting with high‐throughput sequencing data from previous selections, a DDIM is trained to produce novel sequences with high affinity binding. Experimental validation confirms that most generated sequences are functionally equivalent to the original library members for Bcl‐x L binding and demonstrated comparable binding kinetics and affinity relative to the wildtype and nearest original neighbors. Importantly, this approach generated rare sequences not easily accessible via mutation and directed evolution. These results indicate that DDIMs can complement and expand directed evolution data, efficiently exploring underrepresented regions of sequence space. This approach provides a broadly applicable framework for accelerating ligand discovery and optimizing molecular properties across diverse targets.

Qi, Pearl [Mork Family Department of Chemical Engi↗

DOE OSTI2023

Tools and Methods for Optimization of Nuclear Plant Outages

Refueling outages are one of the most challenging phases in a nuclear power plants (NPP) operating cycle. Refueling outages are extremely costly for a NPP due to the large amount of required resources and because of lost revenue due to plant being off the grid. Outage durations have steadily decreased across the industry over that last few decades primarily due to improved planning and coordination, but there are still many plants that struggle to meet the performance metrics accomplished by other utilities. Schedule resilience is one of the issues. NPP outages require scheduling thousands of activities in a duration of around 30 days on average. Outage staff begin working on the schedule more than a year ahead of the outage start and make every effort to build a robust schedule. Despite the robust and detailed planning, once the outage starts, numerous emergent issues typically appear along with schedule delays requiring continuous replanning and adjusting. When schedule disruption occurs during an outage, plant staff make urgent efforts to recover but often not able to maintain the planned outage duration. These outage delays can cost a utility several million dollars per day. Tools that could help outage schedulers create a more resilient schedule and allow them to optimally reschedule emergent work could significantly reduce outage delays. One key aspect of creating a resilient schedule is to have accurate estimates for activity duration. Another important outage scheduling capability is the ability to schedule emergent work with minimal disruption. The Optimization of Outage Activities project under the Risk-Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program focuses on developing tools and methods to support nuclear power plants with optimization of outage schedules. The goal of the outage optimization is the completion of all planned and emergent outage activities as fast as possible while maintaining highest level of safety. This report describes the initial development of tools to support outage management that leverage computational and machine learning methods developed in other RISA and LWRS projects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗