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At least 811 records · Page 45

Approach for energy efficient building design during early phase of design process

Energy consumption in the building sector is about 40% of total energy consumed globally and is trending upwards, along with its contribution to greenhouse gas (GHG) emissions. Given the adverse impacts of GHG emissions, it is crucial to integrate energy efficiency into building designs. The most significant opportunities for enhancing energy performance are present during the initial phases of building design, when there is less impact of other design constraints. Various tools exist for simulating different design options and providing feedback in terms of energy consumption and comfort parameters. These simulation outputs must then be analyzed to derive design solutions. This paper presents an innovative approach that utilizes user input parameters, processes them through cloud computing, and outputs easily understandable strategies for energy-efficient building design. The methodology employs Asynchronous Distributed Task Queues (DTQ) - a more scalable and reliable alternative to conventional speedup techniques-for conducting parametric energy simulations in the cloud. The goal of this approach is to assist design teams in identifying, visualizing, and prioritizing energy-saving design strategies from a range of possible solutions for each project. Furthermore, a tool ‘eDOT’ has been developed utilizing the discussed methodology. Unlike existing tools, eDOT leverages artificial intelligence to dynamically generate and provide design strategies during the early phases of design process. By simplifying the simulation process, eDOT enables design teams to make informed, data-driven decisions without needing to interpret complex simulation outputs. A case study simulated for two locations is provided in this paper to demonstrate the effectiveness of eDOT, further underscoring its practical impact on energy-efficient building design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Systems Innovation: Modernization & Efficiencies for ESH&Q Reviews

Environmental compliance reviews at INL have traditionally been managed through fragmented systems, relying on multiple spreadsheets and manual processes. This inefficiency led to time-consuming status updates and redundant tasks, such as manually sending reminder emails and transferring data from Excel to the Environmental Review Process (ERP). Initial attempts to streamline these processes using Power Automate and Excel revealed significant limitations, necessitating a more comprehensive solution. To address these immediate inefficiencies, automated workflows were developed using Power Automate. These workflows were designed to send scheduled status update reminders and capture responses through standardized forms, with submitted data flowing directly into centralized Excel trackers. This automation reduced the administrative burden, improved data accuracy, and enabled faster, more consistent reporting. Specifically, email automation achieved a 65% efficiency gain, while data integration saw a 48% improvement, resulting in 91% of project statuses being updated within two months. Despite the improvements brought by Power Automate, the fragmented nature of the review processes persisted. To further enhance efficiency and accuracy, the Integrated Review Tool (IRT) was developed. The IRT aims to centralize review initiation and connect team systems, creating an interconnected data infrastructure that preserves team autonomy while enhancing overall efficiency. This tool automates email reminders, centralizes reviews, and streamlines data integration, significantly improving the accuracy and efficiency of environmental compliance reviews. The design and development of the IRT involved advanced systems methodology, process mapping, project management, and collaboration with subject matter experts. The minimum viable product design is 100% complete, and system development is currently underway, with expected outcomes including a centralized entry point for all ESH&Q reviews, automated routing, real-time tracking and analytics, AI integration, and a user-friendly interface. This project demonstrates the potential of leveraging automation and integrated systems to enhance efficiency, accuracy, and decision-making in environmental reporting and compliance processes at INL.

99 - GENERAL AND MISCELLANEOUS↗

BETO 2021 Peer Review - Continuous Enzymatic Hydrolysis Development (CEHD) WBS 2.4.1.101

The Continuous Enzymatic Hydrolysis Development (CEHD) project aims to reduce the cost and commercialization scale-up risks of biorefinery sugar-lignin production through development of a deployable continuous enzymatic hydrolysis (CEH) process. Through the use of external cross flow membrane filtration loops coupled to enzymatic hydrolysis (EH) reactors, pretreated biomass solids and enzymes are retained for reaction while solubilized product sugars are removed in situ, with high extents of conversion achieved through a series of reactor-membrane unit stages. The CEHD project is focused on advancing CEH as a transformational, process-intensified, lower-cost method for producing soluble clarified biomass sugars and insoluble lignin-rich streams than traditional batch enzymatic hydrolysis (BEH). The project's primary objective is to reduce the cost of CEH to be compellingly lower than conventional BEH, 10% lower in year 1 and 20% lower in year 3 (end of project). A related objective is to expand CEH's operating envelope to increase process efficiency. Through more thorough de-risking and demonstration of CEH, in conjunction with building a suite of modeling and optimization tools that allow for more facile rigorous in silico evaluation of novel CEH designs and modalities, this project intends to elevate industry interest in adopting CEH as an improvement over conventional batch processing. This project was merit reviewed in FY20. It's now in its first year of a new 3-year plan spanning FY21-FY23.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

An application of computer aided requirements analysis to a real time deep space system

The entire procedure of incorporating the requirements and goals of a space flight project into integrated, time ordered sequences of spacecraft commands, is called the uplink process. The Uplink Process Control Task (UPCT) was created to examine the uplink process and determine ways to improve it. The Problem Statement Language/Problem Statement Analyzer (PSL/PSA) designed to assist the designer/analyst/engineer in the preparation of specifications of an information system is used as a supporting tool to aid in the analysis. Attention is given to a definition of the uplink process, the definition of PSL/PSA, the construction of a PSA database, the value of analysis to the study of the uplink process, and the PSL/PSA lessons learned.

Farny, A. M.↗

Investigation of etching techniques for superconductive Nb/Al-Al2O3/Nb fabrication processes

Wet etching, CF4 and SF6 reactive ion etching (RIE), RIE/wet hybrid etching, Cl-based RIE, ion milling, and liftoff techniques have been investigated for use in superconductive Nb/Al-Al2O3/Nb fabrication processes. High-quality superconductor-insulator-superconductor (SIS) junctions have been fabricated using a variety of these etching methods; however, each technique offers distinct tradeoffs for a given process an wafer design. In particular, it was shown that SF6 provides an excellent RIE chemistry for low-voltage anisotropic etching of Nb with high selectivity to Al. The SF6 tool has greatly improved the trilevel resist junction insulation process. Excellent repeatability, selectivity with respect to quartz, and submicron resolution make Cl2 + BCl3 + CHCl3 RIE a very attractive process for trilayer patterning.

Lichtenberger, A. W.↗

Chemical Hygiene Program

The Chemical Management Team is responsible for ensuring compliance with the OSHA Laboratory Standard. The program at Lewis Research Center (LeRC) evolved over many years to include training, developing Standard Operating Procedures (SOPS) for each laboratory process, coordinating with other safety and health organizations and teams at the Center, and issuing an SOP binder. The Chemical Hygiene Policy was first established for the Center. The Chemical Hygiene Plan was established and reviewed by technical, laboratory and management for viability and applicability to the Center. A risk assessment was conducted for each laboratory. The laboratories were prioritized by order of risk, higher risk taking priority. A Chemical Management Team staff member interviewed the lead researcher for each laboratory process to gather the information needed to develop the SOP for the process. A binder containing the Chemical Hygiene Plan, the SOP, a map of the laboratory identifying the personal protective equipment and best egress, and glove guides, as well as other guides for safety and health. Each laboratory process has been captured in the form of an SOP. The chemicals used in the procedure have been identified and the information is used to reduce the number of chemicals in the lab. The Chemical Hygiene Plan binder is used as a training tool for new employees. LeRC is in compliance with the OSHA Standard. The program was designed to comply with the OSHA standard. In the process, we have been able to assess the usage of chemicals in the laboratories, as well as reduce or relocate the chemicals being stored in the laboratory. Our researchers are trained on the hazards of the materials they work with and have a better understanding of the hazards of the process and what is needed to prevent any incident. From the SOP process, we have been able to reduce our chemical inventory, determine and implement better hygiene procedures and equipment in the laboratories, and provide specific training to our employees. As a result of this program, we are adding labeling to the laboratories for emergency responders and initiating a certified chemical user program.

Mayor, Antoinette C.↗

Scout: An AI-Driven Tool for Cyber Threat Report Creation

This talk will introduce Scout, an AI-driven tool designed to enhance the efficiency of cyber threat report creation. Attendees will learn how Scout leverages advanced AI technologies to streamline the reporting process, thereby enabling faster and more reliable threat assessments.

99 - GENERAL AND MISCELLANEOUS↗

Environmental control and life support system analysis tools for the Space Station era

This paper describes the concept of a developing emulation, simulation, sizing, and technology assessment program (ESSTAP) which can be used effectively for the various functional disciplines (structures, power, ECLSS, etc.) beginning with the initial system selection and conceptual design processes and continuing on through the mission operation and growth phases of the Space Station for the purpose of minimizing overall program costs. It will discuss the basic requirements for these tools, as currently envisioned for the Environmental Control and Life Support System (ECLSS), identifying their intended and potential uses and applications, and present examples and status of several representative tools. The development and applications of a Space Station Atmospheric Revitalization Subsystem (ARS) demonstration model to be used for concent verification will also be discussed.

Blakely, R. L.↗

Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗

NASA's New Approach for Evaluating Risk Reduction Due to Space Shuttle Upgrades

As part of NASA's intensive effort to incorporate quantitative risk assessment (QRA) tools in the Agency's decision-making process concerning Space Shuttle risk, NASA has developed a powerful risk assessment tool called the Quantitative Risk Assessment System (QRAS). The QRAS is a tool designed to estimate Space Shuttle risk and evaluate Space Shuttle upgrades. This paper presents an overview of the QRAS with focus on its application for evaluating the risk reduction due to proposed Space Shuttle upgrades. The application includes a case study from the Space Shuttle main engine (SSME). The QRAS overview section of the paper includes the QRAS development process, the technical approach to model development, the QRA quantification methods and techniques, and observations concerning the complex modeling involved in QRAS. The application section of the paper describes a practical case study using QRAS models for evaluating critical Space Shuttle Program upgrades, specifically a proposed SSME nozzle upgrade. This paper presents the method for evaluating the proposed upgrade by comparing the current nozzle (old design with well-established probabilistic models) to the channel wall nozzle (new design at the preliminary design level).

Safie, Fayssal M.↗

Conflict-free trajectory planning for air traffic control automation

As the traffic demand continues to grow within the National Airspace System (NAS), the need for long-range planning (30 minutes plus) of arrival traffic increases greatly. Research into air traffic control (ATC) automation at ARC has led to the development of the Center-TRACON Automation System (CTAS). CTAS determines optimum landing schedules for arrival traffic and assists controllers in meeting those schedules safely and efficiently. One crucial element in the development of CTAS is the capability to perform long-range (20 minutes) and short-range (5 minutes) conflict prediction and resolution once landing schedules are determined. The determination of conflict-free trajectories within the Center airspace is particularly difficult because of large variations in speed and altitude. The paper describes the current design and implementation of the conflict prediction and resolution tools used to generate CTAS advisories in Center airspace. Conflict criteria (separation requirements) are defined and the process of separation prediction is described. The major portion of the paper will describe the current implementation of CTAS conflict resolution algorithms in terms of the degrees of freedom for resolutions as well as resolution search techniques. The tools described in this paper have been implemented in a research system designed to rapidly develop and evaluate prototype concepts and will form the basis for an operational ATC automation system.

Slattery, Rhonda↗

A Data Deposition Platform for Sharing Nuclear Magnetic Resonance Data

Nuclear magnetic resonance (NMR) data are rarely deposited in open databases, leading to loss of critical scientific knowledge. Existing data reporting methods (images, tables, lists of values) contain less information than raw data, and are poorly standardized. Together, these issues limit FAIR (findable, accessible, interoperable, reusable) access to these data, which in turn creates barriers for compound dereplication and the development of new data-driven discovery tools. Existing NMR databases are either not designed for natural products data, or employ complex deposition interfaces that disincentivize deposition. Journals, including the Journal of Natural Products (JNP), are now requiring data submission as part of the publication process, creating the need for a streamlined, user-friendly mechanism to deposit and distribute NMR data. Recently, our team reported the development of the Natural Products Magnetic Resonance Database (NP-MRD; www.np-mrd.org). Here in this paper we present a new data deposition platform for the NP-MRD project that is designed to enable users to deposit NMR data for published or submitted manuscripts in under five minutes. This platform includes a suite of automated data extraction and standardization tools, together with a simple-to-use web-based interface and detailed error reporting to simplify the data deposition process and is available at www.np-mrd.org/submissions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

The IDAES process modeling framework and model library—Flexibility for process simulation and optimization

Abstract Energy systems and manufacturing processes of the 21st century are becoming increasingly dynamic and interconnected, which require new capabilities to effectively model and optimize their design and operations. Such next generation computational tools must leverage state‐of‐the‐art techniques in optimization and be able to rapidly incorporate new advances. To address these requirements, we have developed the Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform, which builds on the strengths of both process simulators (model libraries) and algebraic modeling languages (advanced solvers). This paper specifically presents the IDAES Core Modeling Framework (IDAES‐CMF), along with a case study demonstrating the application of the framework to solve process optimization problems. Capabilities provided by this framework include a flexible, modifiable, open‐source platform for optimization of process flowsheets utilizing state‐of‐the‐art solvers and solution techniques, fully open and extensible libraries of dynamic unit operations models and thermophysical property models, and integrated support for superstructure‐based conceptual design and optimization under uncertainty.

42 ENGINEERING↗

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗

RxnRover/CyRxnOpt

CyRxnOpt aims to provide a single software interface to various optimization algorithms, mainly designed for chemical process optimization applications. CyRxnOpt generalizes the optimization process into four high-level “phases”: Installation, Configuration, Training, and Prediction. This allows developers to program to a general interface for each phase of the optimization, simplifying the development of user-friendly tools to lower the barrier of entry into chemical process optimization, especially for automated laboratory workflows which can greatly benefit from access to various optimization techniques. It is also designed so researchers can easily add new or existing algorithms into existing workflows in a user-friendly manner.

Kulathunga, Dulitha Prasanna [Iowa State Universit↗

Modeling and Analysis of Power Processing Systems (MAPPS), initial phase 2

The overall objective of the program is to provide the engineering tools to reduce the analysis, design, and development effort, and thus the cost, in achieving the required performances for switching regulators and dc-dc converter systems. The program was both tutorial and application oriented. Various analytical methods were described in detail and supplemented with examples, and those with standardization appeals were reduced into computer-based subprograms. Major program efforts included those concerning small and large signal control-dependent performance analysis and simulation, control circuit design, power circuit design and optimization, system configuration study, and system performance simulation. Techniques including discrete time domain, conventional frequency domain, Lagrange multiplier, nonlinear programming, and control design synthesis were employed in these efforts. To enhance interactive conversation between the modeling and analysis subprograms and the user, a working prototype of the Data Management Program was also developed to facilitate expansion as future subprogram capabilities increase.

Yu, Y.↗

Theoretical investigation of gas-surface interactions

The goal of this project was to develop computational tools for the calculation of the electronic structure of molecules containing heavy atoms, and to use these tools in the study of catalytic processes, with the overall objective of gaining an understanding of the catalytic process which could be used to design more efficient catalysts. The main catalytic system of interest was the combustion of hydrogen on platinum surfaces. Under this project, a flexible Dirac-Hartree-Fock (DHF) program has been developed, a code to calculate DHF correlation energies at the second-order Moeller-Plesset perturbation (PP2) level is almost complete, and code to include correlation at the MCSCF and MCSCF/MP2 level is planned. The tools so far developed have been validated and used to calibrate some more approximate methods, and applied to investigate the importance of relativistic effects in the bonding of hydrogen to platinum.

Dyall, Kenneth G.↗

A low cost imaging displacement measurement system for spacecraft thermal vacuum testing

A low cost imaging displacement technique suitable for use in thermal vacuum testing was built and tested during thermal vacuum testing of the space infrared telescope facility (SIRTF, later renamed Spitzer infrared telescope facility). The problem was to measure the relative displacement of different portions of the spacecraft due to thermal expansion or contraction. Standard displacement measuring instrumentation could not be used because of the widely varying temperatures on the spacecraft and for fear of invalidating the thermal vacuum testing. The imaging system was conceived, designed, purchased, and installed in approximately 2 months at very low cost. The system performed beyond expectations proving that sub millimeter displacements could be measured from over 2 meters away. Using commercial optics it was possible to make displacement measurements down to 10 (mu)m. An automated image processing tool was used to process the data, which not only speeded up data reduction, but showed that velocities and accelerations could also be measured. Details of the design and capabilities of the system are discussed along with the results of the test on the observatory. Several images from the actual test are presented.

thermal vacuum↗