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At least 127 records · Page 7

IDAES-PSE 1.13.0 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↗

IDAES-PSE 2.3.0 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.. New Features and Models • New diagnostics toolboxes and examples o Tutorial for using the DiagnosticsToolbox o Methods to identify potential evaluation errors in models o SVDToolbox for performing singular value decomposition analysis on models to identify possible degeneracies and poor scaling o DegeneracyHunter for identifying irreducible degenerate sets in models • Model for solid-liquid separation which takes two inputs (solid and liquid streams) and produces three outlets (solids, liquid entrained with solids and pure liquid) • Example of temperature swing adsorption in models_extra Deprecation Warnings • With the update to Pyomo 6.7.0, the plate heat exchanger model has begun failing tests on some CI platforms. If this is not addressed by the February release, this model may be removed due to failing tests. See #1294. Offers to help identify the cause and fix this issue are welcome. Improvements and bug fixes • Fixed oversight which precluded using Mixer and Separator models when inherent reactions were present in property package • Added reporting methods to the MSContactor model • Minor corrections in some examples where values were being fixed outside of declared variable bounds

DiagnosticsToolbox,IDAES,PSE,Process Systems Engin↗

IDAES-PSE 2.4.0 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.. Deprecations • Convergence Analysis tool (idaes/core/util/convergence): deprecated in favor of new Parameter Sweep tools. To be removed in v3.0.0. New Beta Capabilities • Parameter Sweep Tool (idaes.core.util.parameter_sweep) o A new API for defining and performing parameter sweep studies on IDAES models has been developed • Diagnostics Tools (idaes.core.util.model_diagnostics) o New methods for identifying duplicate variables and constraints have been added to the diagnostics toolbox o New tools for detecting ill conditioning in Jacobians have been developed and are available in the model_diagnostics module. These provide alternatives to the existing DegeneracyHunter toolbox, and will eventually be merged with this capability, but initial working versions have been provided as beta capabilities for interested users o IpoptConvergenceAnalysis (replaces deprecated Convergence Analysis tool):  A new tool for performing convergence analysis studies that leverages the new Parameter Sweep tools has been developed. This tool allows users to define the input parameters to their model and sampling methods for these (leveraging Pysmo's sampling tools) and to then solve their model across the sampled domains and return a summary of the solver performance (IPOPT only) Improved Models • Thickener model (idaes.models.unit_models.solid_liquid.thickener) o Improved model to include predictive correlations for unit sizing based on settling velocity measurements (steady-state only) • Modular Property Packages o Added general support for calculating critical properties of mixtures using defined Equation of State modules. New API defined for Equation of State modules in order to define the necessary constraints for calculating critical properties (most EoS modules DO NOT support calculation of critical properties (yet)) o Added new methods to Cubic Equation of State module to support calculation of critical properties

DiagnosticsToolbox↗

IDAES-PSE 2.5.0 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 2.5.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New diagnostics check for near-parallel variables and constraints. New diagnostics tools for identifying causes of infeasibility in models. New example for creating a custom model of a liquid-liquid extractor unit operation. Bug Fixes Fixed bug in Gibbs reactor that caused it to appear to have additional spurious degrees of freedom. Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Testing and Robustness Deployed the IDAES Diagnostics Toolbox to confirm that there are no structural or numerical issues in the core model libraries. Additional robustness tests for core model, and some associated improvements in the converge tester class. Fixed a number of issues that were causing unexpected warnings to be emitted during testing. Deprecations and Removals Removed examples for RIPE tool which has not been supported for a number of releases.

AS↗

Artificial Intelligence and Digital Engineering as Enablers for System Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.

42 - ENGINEERING↗

Artificial Intelligence and Digital Engineering as Enablers for Systems Engineering in the Energy Sector

Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world?s energy demands and build energy security.

42 - ENGINEERING↗

Managing Analysis Models in the Design Process

Design of large, complex space systems depends on significant model-based support for exploration of the design space. Integrated models predict system performance in mission-relevant terms given design descriptions and multiple physics-based numerical models. Both the design activities and the modeling activities warrant explicit process definitions and active process management to protect the project from excessive risk. Software and systems engineering processes have been formalized and similar formal process activities are under development for design engineering and integrated modeling. JPL is establishing a modeling process to define development and application of such system-level models.

design↗

Tailoring Enterprise Systems Engineering Policy for Project Scale and Complexity

Space systems are characterized by varying degrees of scale and complexity. Accordingly, cost-effective implementation of systems engineering also varies depending on scale and complexity. Recognizing that systems engineering and integration happen everywhere and at all levels of a given system and that the life cycle is an integrated process necessary to mature a design, the National Aeronautic and Space Administration's (NASA's) Marshall Space Flight Center (MSFC) has developed a suite of customized implementation approaches based on project scale and complexity. While it may be argued that a top-level system engineering process is common to and indeed desirable across an enterprise for all space systems, implementation of that top-level process and the associated products developed as a result differ from system to system. The implementation approaches used for developing a scientific instrument necessarily differ from those used for a space station. .

Cox, Renee I.↗

2nd Generation RLV Risk Definition Program

The 2nd Generation RLV Risk Reduction Mid-Term Report summarizes the status of Kelly Space & Technology's activities during the first two and one half months of the program. This report was presented to the cognoscente Contracting Officer's Technical Representative (COTR) and selected Marshall Space Flight Center staff members on 26 September 2000. The report has been approved and is distributed on CD-ROM (as a PowerPoint file) in accordance with the terms of the subject contract, and contains information and data addressing the following: (1) Launch services demand and requirements; (2) Architecture, alternatives, and requirements; (3) Costs, pricing, and business cases analysis; (4) Commercial financing requirements, plans, and strategy; (5) System engineering processes and derived requirements; and (6) RLV system trade studies and design analysis.

Davis, Robert M.↗

Decision Support Tools Evaluation Report for FAS/PECAD, Version 2.0

Global agricultral intelligence is a key element of decision support eithin the U.S. Department of Agriculture (USDA). Estimeates of production and yield issued by the USDA for both foreign and domestic agriculture are primary sources of information for policy and management decision making. The USDA monitors the major global agricultural commodities through the Production Estimates and Crop Assessment Division (PECAD) of its Foreign Agricultural Service (FAS). Specifically, PECAD iintelligence focuses on global agricultural production and on conditions that affect food security. In conjunction with the USDA, NASA is evaluating the potential for products from NASA's Earth Science Enterprise (ESE) missions to add value to PECAD's decision support tools. NASA is usig a systems engineering approach to evaluate the potential enhancement of PECAD's decision support system (DSS)-first by understanding the components of the system and its input requirements, then by recommending NASA products that may be integrated as system inputs to improve the accuracy, quality, or efficiency of the DSS output. This report documents the evaluation phase of the systems engineering process and includes an examination of the system architecture, operations, and input requirements, as well as an initial assessment of specific ESE measurement systems and products that should be considered for their potential to enhance the PECAD DSS.

Ross, Kenton↗

Risk Analysis and System Trades inthe Mars Sample Return (MSR) Mission

Risk Managenent advocates have long sought to directly influence the early stages of the systems engineering process through a more effective role in system design trade studies. The principal obstacle to this has been the lack of credible ways to represent and quantify mission risk that is, missios return form a probablistic viewpoint-for the project manager and the rest of the design team.

Risk Analysis Mars Sample Return↗

Risk analysis simulation of rover operations for Mars surface exploration

Risk management advocates have long sought to directly influence the early stages of the systems engineering process through a more effective role in system design trade studies. The principal obstacle to this has been the lack of credible ways to represent and quantify mission risk—that is, a combination of the probability of mission success (“system safety”) and science value—for the project manager and the rest of the design team. If it were possible to quantify mission risk, then the effects of proposed mission and system design changes could be calculated, and along with life-cycle costs, could be used to explore the design space more extensively and select better designs. JPL has been working to build the capability to quantify the probability of mission success using a federation of diverse simulations and models, each of which contributes some vital piece of the puzzle. The initial institutional focus has been on Mars surface operations. This ensemble computing framework enables the diverse models and simulations to work together seamlessly. Recent work at JPL has demonstrated the capability to exercise this ensemble from end-to-end using an Oracle-based database to automatically move results from one model/simulation to the next stage in the analysis.

Shishko, Robert↗

A Collaborative Vision for Deep Space Human Exploration

Artemis will be the first cooperative campaign among nations for crewed planetary exploration. This paradigm shift reflects a collaborative vision for deep space human exploration that embraces the concept that, “If you want to go fast, go alone; If you want to go far, go together.” This paper elaborates on the way the National Aeronautics and Space Administration(NASA)is striving to make its Moon to Mars effort a collaborative endeavor for long-term human exploration of deep space and for the international space community. The agency is making great strides in unifying its workforce, mission directorates, technical authorities, and centers behind shared goals and processes. Enhanced communication and a reinvigoration of systems engineering ideals have been a hallmark of that effort, guided by the Moon to Mars Architecture, which defines what NASA aims to accomplish and how it will execute those goals. This interdisciplinary approach ensures the Artemis campaign supports NASA’s engineering, science, and technology development goals. As of September 2024, over 43 nations have signed the Artemis Accords, which establish a common set of principles for peaceful cooperation in civil space exploration. Building off these efforts, NASA has been engaging in separate and distinct discussions about partner contributions to Artemis. International partnerships for the Artemis campaign include long-standing partners as well as agencies with which NASA has only more recently begun collaborating. The Gateway Program is an early example of both –benefitting from partnerships with Canada, Japan, and Europe forged though decades of cooperation on the International Space Station, as well as a new partnership with the United Arab Emirates. The agency’s Moon to Mars Objectives and Architecture unify the NASA workforce with common goals and shared systems-engineering processes. The architecture offers pathways for broader participation from industry, academia, and international partners. The agency evolves this collaborative approach through its annual Architecture Concept Review cycle, seeking input from the NASA workforce, and through workshops, from industry, academia, and the international space community to refine NASA’s roadmap for exploration. Exploring together, NASA and its partners are setting humanity on the path to long-term presence at the Moon and our eventual journey to Mars

Objective↗

NASA Systems Engineering Handbook

This handbook brings the fundamental concepts and techniques of systems engineering to NASA personnel in a way that recognizes the nature of NASA systems and environment. It is intended to accompany formal NASA training courses on systems engineering and project management when appropriate, and is designed to be a top-level overview. The concepts were drawn from NASA field center handbooks, NMI's/NHB's, the work of the NASA-wide Systems Engineering Working Group and the Systems Engineering Process Improvement Task team, several non-NASA textbooks and guides, and material from independent systems engineering courses taught to NASA personnel. Five core chapters cover systems engineering fundamentals, the NASA Project Cycle, management issues in systems engineering, systems analysis and modeling, and specialty engineering integration. It is not intended as a directive. Superseded by: NASA/SP-2007-6105 Rev 1 (20080008301).

Shishko, Robert↗

Using the International Space Station (ISS) Oxygen Generation Assembly (OGA) Is Not Feasible for Mars Transit

A review of two papers on improving the International Space Station (ISS) Oxygen Generation Assembly (OGA) shows that it would not save substantial mass on a Mars transit. The ISS OGA requires redesign for satisfactory operation, even for the ISS. The planned improvements of the OGA for ISS would not be sufficient to make it suitable for Mars, because Mars transit life support has significantly different requirements than ISS. The OGA for Mars should have lower mass, better reliability and maintainability, greater safety, radiation hardening, and capability for quiescent operation. NASA's methodical, disciplined systems engineering process should be used to develop the appropriate system.

Space station↗

Developing Advanced Support Technologies for Planetary Exploration Missions

The United States Vision for Space Exploration calls for sending robots and humans to explore the Earth s moon, the planet Mars, and beyond. The National Aeronautics and Space Administration (NASA) is developing a set of design reference missions that will provide further detail to these plans. Lunar missions are expected to provide a stepping stone, through operational research and evaluation, in developing the knowledge base necessary to send crews on long duration missions to Mars and other distant destinations. The NASA Exploration Systems Directorate (ExSD), in its program of bioastronautics research, manages the development of technologies that maintain human life, health, and performance in space. Using a systems engineering process and risk management methods, ExSD s Human Support Systems (HSS) Program selects and performs research and technology development in several critical areas and transfers the results of its efforts to NASA exploration mission/systems development programs in the form of developed technologies and new knowledge about the capabilities and constraints of systems required to support human existence beyond Low Earth Orbit. HSS efforts include the areas of advanced environmental monitoring and control, extravehicular activity, food technologies, life support systems, space human factors engineering, and systems integration of all these elements. The HSS Program provides a structured set of deliverable products to meet the needs of exploration programs. these products reduce the gaps that exist in our knowledge of and capabilities for human support for long duration, remote space missions. They also reduce the performance gap between the efficiency of current space systems and the greater efficiency that must be achieved to make human planetary exploration missions economically and logistically feasible. In conducting this research and technology development program, it is necessary for HSS technologists and program managers to develop a common currency for decision making and the allocation of funding. A high level assessment is made of both the knowledge gaps and the system performance gaps across the program s technical project portfolio. This allows decision making that assures proper emphasis areas and provides a key measure of annual technological progress, as exploration mission plans continue to mature.

Berdich, Debra P.↗

Developing Advanced Human Support Technologies for Planetary Exploration Missions

The United States Vision for Space Exploration calls for sending robots and humans to explore the Earth's moon, the planet Mars, and beyond. The National Aeronautics and Space Administration (NASA) is developing a set of design reference missions that will provide further detail to these plans. Lunar missions are expected to provide a stepping stone, through operational research and evaluation, in developing the knowledge base necessary to send crews on long duration missions to Mars and other distant destinations. The NASA Exploration Systems Directorate (ExSD), in its program of bioastronautics research, manages the development of technologies that maintain human life, health, and performance in space. Using a system engineering process and risk management methods, ExSD's Human Support Systems (HSS) Program selects and performs research and technology development in several critical areas and transfers the results of its efforts to NASA exploration mission/systems development programs in the form of developed technologies and new knowledge about the capabilities and constraints of systems required to support human existence beyond Low Earth Orbit. HSS efforts include the areas of advanced environmental monitoring and control, extravehicular activity, food technologies, life support systems, space human factors engineering, and systems integration of all these elements. The HSS Program provides a structured set of deliverable products to meet the needs of exploration programs. These products reduce the gaps that exist in our knowledge of and capabilities for human support for long duration, remote space missions. They also reduce the performance gap between the efficiency of current space systems and the greater efficiency that must be achieved to make human planetary exploration missions economically and logistically feasible. In conducting this research and technology development program, it is necessary for HSS technologists and program managers to develop a common currency for decision making and the allocation of funding. A high level assessment is made of both the knowledge gaps and the system performance gaps across the program s technical project portfolio. This allows decision making that assures proper emphasis areas and provides a key measure of annual technological progress, as exploration mission plans continue to mature.

Berdich, Debra P.↗

Socio-Technical Perspective on Interdisciplinary Interactions During the Development of Complex Engineered Systems

This study investigates interdisciplinary interactions that take place during the research, development, and early conceptual design phases in the design of large-scale complex engineered systems (LaCES) such as aerospace vehicles. These interactions, that take place throughout a large engineering development organization, become the initial conditions of the systems engineering process that ultimately leads to the development of a viable system. This paper summarizes some of the challenges and opportunities regarding social and organizational issues that emerged from a qualitative study using ethnographic and survey data. The analysis reveals several socio-technical couplings between the engineered system and the organization that creates it. Survey respondents noted the importance of interdisciplinary interactions and their benefits to the engineered system as well as substantial challenges in interdisciplinary interactions. Noted benefits included enhanced knowledge and problem mitigation and noted obstacles centered on organizational and human dynamics. Findings suggest that addressing the social challenges may be a critical need in enabling interdisciplinary interactions

McGowan, Anna-Maria R.↗