Search NASA⌕ Search

SEARCH · Search NASA

Results for “early design”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Design-Space Data: Informing Common Design Decisions with Pre-Simulated Data

Design Space Exploration (DSE) analysis techniques represent a data-centric approach to integrating performance analysis in early design phases when there is the greatest potential to cheaply improve the energy efficiency of a building. We focus on a novel extension of DSE called Universal Design Space Exploration (UDSE), which leverages massive databases of pre-simulated analysis that represent all possible outcomes of common analysis workflows. These databases, called Design Spaces, become “universal” when a single pre-simulated design space can be re-applied to future unknown projects. Unlike current simulation methods, which require a design to exist before it can be analyzed and often take minutes or hours to simulate, UDSE leverages pre-simulation to deliver rapid and relevant insight as new designs are conceptualized. The data underpinning UDSE enables advanced statistical and Artificial Intelligence methods, allowing UDSE to deliver a greater understanding of the larger problem being explored, rather than simply delivering analysis of several pre-conceived design options. We believe that UDSE can provide instantaneous, relevant analysis for all building design projects at negligible cost. This paper has two main goals, to develop a relevant Universal Design Space that showcases the potential of UDSE and to release this data freely to industry and academia; thereby lowering the barrier to entry to digital literacy in statistics, ML and AI within the architecture, engineering, construction (AEC) industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Reliability-Informed Economic and Energy Evaluation for Design for Remanufacturing: A Case Study on a Hydraulic Manifold

Design for Remanufacturing (DfRem) is an attractive approach for sustainable product development. Evaluation of DfRem strategies, from both economic and environmental perspectives, at an early design stage can allow the designers to make informed decisions when choosing the best design option. Studying the long-term implications of a particular design scenario requires quantifying the benefits of remanufacturing for multiple life cycles while considering the reliability of the product. In addition to comparing designs on a one-to-one basis, we find that including reliability provides a different insight into comparing design strategies. We present a reliability-informed cost and energy analysis framework that accounts for product reliability for multiple remanufacturing cycles within a certain warranty policy. The variation of reuse rate over successive remanufacturing cycles is formulated using a branched power-law model which provides probabilistic scenarios of reusing or replacing with new units. To demonstrate the utility of this framework, we use the case study of a hydraulic manifold, which is a component of a transmission used in some agricultural equipment, and use real-world field reliability data to quantify the transmission’s reliability. Three design improvement changes are proposed for the manifold and we quantify the costs and energy consumption associated with each of the design changes for multiple remanufacturing cycles.

design for remanufacturing↗
DOE OSTI2021

Cabin Thermal Management Analysis for SuperTruck II Next-Generation Hybrid Electric Truck Design

In this article, we present a multistage, coupled thermal management simulation approach, informed by physical testing where available, to aid design decisions for PACCAR's SuperTruck II hybrid truck cabin concept. Focus areas include cabin insulation, battery sizing, and sleeper curtain position, as well as heating, ventilating, and air-conditioning (HVAC) component and accessory configurations, to maintain or improve thermal comfort while saving energy. The authors analyzed weather data and determined the national vehicle miles traveled weighted temperature and solar conditions for long-haul trucks. Example weather day profiles were selected to approximate the 5th and 95th percentile weighted conditions. A daylong drive cycle was developed to impose appropriate external wind conditions during rest and driving periods. Using the National Renewable Energy Laboratory's vehicle HVAC modeling and simulation tool VTCab, HVAC load design trade-off studies for the new truck geometry concept were completed. Parameters analyzed included effects of paint color, insulation, glass transmissivity, and curtain location. Simulation results helped with early design material selections for efficient cabin climate control. A detailed three-dimensional computer-aided engineering (CAE), computational fluid dynamics (CFD), radiation, and human physiology co-simulation, referred to in this article as CAE Thermal-CFD, was used to evaluate thermal comfort and energy impacts of diffuser configurations and air supply settings in driving and hoteling modes. Analysis revealed that it is more difficult to heat the cabin in hoteling mode during the winter than to cool the space in the summer. This seasonal load profile drives the requirement of additional energy storage for heating comfort. To determine the battery capacity requirement, multiday HVAC operation drive cycle simulations were then completed, showing that a 15-kWh battery would be required for HVAC operation during hoteling. Results helped reduce cabin thermal loads, determine component sizing requirements, and improve occupant comfort to save fuel and contribute to the economic viability of the hybrid system.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Medium and Heavy Duty Vehicle Powertrain Electrification and Fleet Demonstration

The Contract Award Grant # EE0007513 dated 2 June, 2016 is for the design, development and demonstration of medium duty package delivery vehicles that will result in a 100% increase in fuel economy as measured in miles per gallon. The project was proposed in 3 phases over two budget periods. The Phases were: 1. Modeling and Simulation – This phase was completed and formed the basis of the specifications for the design and build of the physical systems. The modeling and simulation was conducted by AVL and used real world package delivery routes that AVL mapped. The motors, battery pack, range extender and balance of plant support systems were modeled and iterated until a system with the desired fuel economy improvement was realized. Early design of the major subsystems using the actual vehicle space constraints was also completed. This phase was successfully completed in May of 2017. 2. 1st Build and FE Confirmation - This phase was completed and resulted in the final design, release, procurement and build of all major vehicle systems for commissioning into the first vehicle. The work was a partnered effort between McLaren and AVL. McLaren built the eAxle system while AVL built the range extender and integrated the range extender, battery and balance of plant sub-systems into the first vehicle with a control system to make it operate. Prior to the end of this phase a real world HIL system test gave evidence that the fuel economy improvement would be achieved in the real world. This phase was exited with a 7 month delay due mostly to procurement and supply base issues and ended in May, 2018. 3. Final Build and Demonstration - This phase included the final build and commissioning of the four program vehicles and the operation of a demonstration on a set of routes near San Diego California. During this phase, a multitude of issues arose in different systems in the vehicle. These issue resolution exercises were quite complex and caused repeated delays but were all successfully completed. It should also be noted that an early commercialization analysis resulted in the conclusion that the complexity of the system would not make it cost effective, leading to the start of a follow-on design that used newly available component technologies to specify a more cost effective system. This design will be repurposed and put into demonstration on a separately (non-DOE) funded program. It was decided and agreed with DOE that this phase should be considered completed. The knowledge and know-how gained on this program has been incorporated into and transferred to the new program. This phase and the entire program was considered closed on June 1, 2021.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

An open source fast fluid dynamics model for data center thermal management

Although computational fluid dynamics (CFD) has been widely adopted to improve data center thermal management, the high computational demand limits its applications, such as multivariate optimal design and operation. Fast fluid dynamics (FFD), which has been applied for fast airflow simulation, shows great potential. However, few research applied FFD for optimal design and operation of data center thermal management. This research improves the FFD model for data centers and conducts a comprehensive evaluation and demonstration. First, the FFD model is improved by solving the advection and diffusion equations together using an upwind scheme instead of a semi-Lagrangian advection solver in the conventional FFD model. Second, new features for data centers are added, such as a pressure correction method to simulate plenum airflow and dynamic boundary conditions for IT racks. The new FFD model is first validated with two indoor environment cases and the results show that the new FFD model has slightly better overall prediction accuracy and faster speed compared to the conventional FFD model. It is also observed that both FFD models achieve acceptable accuracy, except for a few localized disparities with experimental data, which might be due to simplified handling of turbulence viscosity near the boundaries. Furthermore, validation with a real data center shows that the FFD model achieves a similar level of accuracy as CFD when compared to the experimental measurements with some level of uncertainties. It is then demonstrated for data center optimal design and operation, which saves 53.4–58.8% of annual energy while still meeting the thermal requirements. In conclusion, with a much faster speed and comparable accuracy compared to CFD, the FFD model parallelized on a graphics processing unit is promising for practical model-based data center early design and operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Reliability-based hull geometry optimisation of a point-absorber wave energy converter with power take-off structural reliability objectives

Recent studies have focused on optimising wave energy converter (WEC) designs, maximising their power performance and techno-economic feasibility. Reliability has yet to be fully considered in these formulations, despite its impact on cost and performance. In this study, this gap is addressed by developing a reliability-based design optimisation framework for WEC hull geometries to explore the trade-off between power performance and power take-off (PTO) system damage equivalent loading (DEL). Optimised hull geometries for two sites are considered (from the centre of the North Sea and off the west coast of Norway), and two directions of motions (heave and surge). Results indicate that site characteristics affect the potential power production and DEL for an optimal WEC design. These are also affected by the direction of motion for power extraction, which also significantly changes optimal hull shape characteristics. Optimal surging WEC designs have edges facing oncoming wave directions, while heaving WECs have pointed bottoms, both to streamline movement. Larger, more convex WECs result in greater power production and DEL, while smaller, more concave WECs result in lesser power production and DEL. These findings underline the importance of considering WEC hull geometry in early design processes to optimise cost, power production, and reliability.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Integration of Safety, Security, and Safeguards During Design and Operations: A Technical Assessment and Regulatory Considerations for Advanced Reactor and Advanced Fuel Fabrication Facilities

This report presents the current state of knowledge, technology, methodologies, and tools that could be implemented to realize the robust integration of safety, security, and safeguards (3S) for advanced nuclear reactors (ARs) and advanced nuclear fuel cycle facilities. This report was motivated by the global development of ARs which are expected to play a key role in meeting domestic energy and climate objectives. Domestically, with many ARs in the early design phase, the integration of 3S provides an opportunity to achieve risk reduction while using less resources than traditional light water reactors by leveraging interdependencies and synergies between each domain. In addition, domestic policy considerations encourage the convergence of each 3S domain through facility design and operations. Therefore, there is a need to better understand the interdependencies and integration between 3S across ARs and advanced reactor fuel cycle facilities’ lifecycles including design, construction, and operational phases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Visual Modeling for Complex System Valuation: Implementation Guidance

Within the Transactive Systems Program (TSP) at Pacific Northwest National Laboratory (PNNL) the need to incorporate a valuation analysis design early within the research process of transactive energy systems led to development of a valuation methodology. This methodology allows the modeling of economic exchanges within a complex system and supports the evaluation of individual stakeholder economic outcomes in addition to systemwide costs and benefits. The use of visual modeling practices enables the research team to reach common understanding and agreement on the analysis design within the complex system. While this methodology was developed for the valuation of transactive energy systems, it can be applied to any complex system where a granular economic analysis is desired. It allows for the inclusion of equity analyses and ties individual activities and microeconomic outcomes with the systemwide macroeconomic impacts. This document serves as implementation guidance for analysts planning to deploy the methodology within a research study. The appendixes provide specific guidance on how this methodology is deployed within the TSP at PNNL for analysts seeking guidance for deployment within that context.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Investigation of Main Bearing Fatigue Estimate Sensitivity to Synthetic Turbulence Models Using a Novel Drivetrain Model Implemented in OpenFAST

ABSTRACT A coupled medium‐fidelity drivetrain model is developed and implemented in OpenFAST for a 10‐MW land‐based reference turbine. The implementation is verified against a fully coupled multibody wind turbine model, including a detailed drivetrain. The new model can simultaneously and accurately estimate main bearing loads and represent elastic bending of the drivetrain. It has low computational cost and is useful for early design phases, sensitivity analyses and complex systems like wind farms (where computational expense must be expended elsewhere). Here, the model is implemented for a monopile offshore wind turbine and used to investigate the sensitivity of main bearing basic rating life to different synthetic turbulence models. Large‐eddy simulations (LES) targeting stable, neutral, and unstable atmospheric conditions at below‐, near‐ and above‐rated wind speeds are used as a reference. The turbulence models recommended by the International Electrotechnical Commission, the Mann spectral tensor model, and the Kaimal spectral model with exponential coherence are fitted to the LES data. Additionally, a constrained turbulence generator, PyConTurb (short for Python Constrained Turbulence ), based on LES data, is applied in the aero‐hydro‐servo‐elastic simulations. Taking PyConTurb as the baseline, the Kaimal model significantly underestimates fatigue of the downwind main bearing, with between 10% and 40% less damage. The Mann model also underestimates the downwind main bearing fatigue by up to 30%. The upwind main bearing damage is driven by mean loads, and differences between models are less significant, although the trends are similar. Reasons for these discrepancies are investigated and attributed to differences in spatial and temporal variations among the turbulence models.

17 WIND ENERGY↗
DOE OSTI2020

The impacts of building characteristics, social psychological and cultural factors on indoor environment quality productivity belief

Indoor environmental quality (IEQ) plays a key role in determining occupants' productivity at work; however, analyses of the interconnected factors among building physical, attitudinal, social and demographic components in one study are lacking. To fill this research gap, this study investigates these interconnected factors' influence on occupants’ IEQ-productivity belief, defined as a personal, subjective evaluation of the linkage between the impacts of five IEQ aspects (the quality of indoor temperature, air, natural and electric lighting, and acoustics) and productivity. A cross-sectional survey data was collected in university offices from six countries (Brazil, Italy, Poland, Switzerland, Taiwan and the U.S.). Results of multiple linear regression models indicate that IEQ satisfaction is the strongest positive predictor of the IEQ-productivity belief and this relationship is stronger in private offices. Country of residence is the second primary predictor. Several attitudinal-behavioral factors, including thermal comfort, perceived ease of controlling indoor environmental features, and attitudes toward sharing controls are all positively associated with IEQ-productivity belief. Interestingly, the level of control accessibility to light switches has the strongest impact as opposed to other controls. On the other hand, group norms and conformity intention are not significant predictors. Regarding demographics, men are more likely than women to perceive the IEQs to have positive impacts on their productivity, without considering other variables in the regression model; however, women are more likely than men to consider all IEQs as having positive impacts on productivity, after considering other variables. Furthermore, our findings provide suggestions for prioritizing wellness in the workplace since the early design stage.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

A Proxy Method to Bridge LCA Data Gaps Using Automated Material Classification and Probabilistic Under-Specification

Life cycle assessments (LCAs) are essential for understanding the environmental impacts of material production. However, gaps in life cycle inventory (LCI) data for material and chemical inputs present a key challenge for LCA practitioners, especially in the early design stages. Strategies for filling in these gaps require additional time and expertise, which can hinder the LCA’s completion. This study combined automatic material classification and probabilistic under-specification to create a time-efficient method to fill material LCI data gaps. To illustrate the proposed method, proxy environmental impact distributions were generated using publicly available material LCI data classified into the ChemOnt chemical taxonomy using the open-source chemical classification software ClassyFire. Input materials with data gaps were then classified into the same taxonomy, where proxy environmental impact values could be selected from the available distributions to quickly fill in any data gaps. Although these methods were applied to classify material production processes available in the Federal LCA Commons and Ecoinvent databases, they can be applied to any LCA database. This study shows that classifying materials by their chemical structure produces taxonomies with increased granularity relative to industrial classification, improving the ability of under-specified proxy data to be used for differentiating the environmental impacts of competing designs.

biological databases↗
DOE OSTI2024

The crucial role of diagnostics in achieving ignition on the National Ignition Facility (NIF)

Well over 100 diagnostics can operate on the National Ignition Facility (NIF) as a result of several decades of development on NIF, and before that on Nova, OMEGA, and earlier LLNL lasers. A subset of these have guided the approach to achieving ignition on the NIF in 2022 [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129(7), 075001 (2022)]. Achieving ignition on NIF has required many types of experiments with this core set of diagnostics, some constraining known unknowns and some revealing surprises—arguably unknown unknowns. Early design work realized that the extreme precision required for ignition on NIF would require fine-tuning by experiment, that is, measuring and adjusting known unknowns. Many examples are given where the use of the core set of ignition diagnostics in experimental arrangements called platforms demonstrated control of the key theoretical parameters defined as shape, adiabat, velocity, and mix. The direction of the adjustments to input conditions is found either by trend analysis or, in many cases, by observing from the diagnostic data the direction to make an adjustment. In addition, diagnostics have revealed some unexpected or neglected known issues, which degrade performance, or unexpected issues, unknown unknowns. Some of these factors had been previously considered, but underestimated or difficult to calculate at the time. The overall methodology can be described as a variant of Popper's falsifiability philosophy [K. Popper, The Logic of Scientific Discovery (Hutchinson, 1974)]. This paper summarizes the role of ignition diagnostics in terms of falsification or validation of theory or experimental setup as well as uncovering unexpected issues. The journey to ignition started in the seventies with a 1-µm wavelength laser producing disastrous results. Diagnostics have guided us to the recent multi-decadal goal of demonstrating ignition and burn in the laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Running Ensemble Workflows at Extreme Scale: Lessons Learned and Path Forward

The ever-increasing volumes of scientific data combined with sophisticated techniques for extracting information from them have led to the increasing popularity of ensemble workflows which are a collection of runs of individual workflows. A traditional approach followed by scientists to run ensembles is to rely on simple scripts to execute different runs and manage resources. This approach is not scalable and is error-prone, thereby motivating the development of workflow management systems that specialize in executing ensembles on HPC clusters. However, when the size of both the ensemble and the target system reach extreme scales, existing workflow management systems face new challenges that hamper their efficient execution. In this paper, we describe our experience scaling an ensemble workflow from the computational biology domain from the early design stages to the execution at extreme scale on Summit, a leadership class supercomputer at the Oak Ridge National Laboratory. We discuss challenges that arise when scaling ensembles to several million runs on thousands of HPC nodes. We identify challenges with composition of the ensemble itself, its execution at large scale, post-processing of the generated data, and scalability of the file system. Based on the experience acquired, we develop a generic vision of the capabilities and abstractions to add to existing workflow management systems to enable the execution of ensemble workflows at extreme scales. We believe that the understanding of these fundamental challenges will help application teams along with workflow system developers with designing the next generation of infrastructure for composing and executing extreme-scale ensemble workflows.

Mehta, Kshitij↗
DOE OSTI2024

First demonstration of 30 eVee ionization energy resolution with RICOCHET germanium cryogenic bolometers

The future RICOCHET experiment aims to search for new physics in the electroweak sector by measuring the Coherent Elastic Neutrino-Nucleus Scattering process from reactor antineutrinos with high precision down to the sub-100 eV nuclear recoil energy range. While the RICOCHET collaboration is currently building the experimental setup at the reactor site, it is also finalizing the cryogenic detector arrays that will be integrated into the cryostat at the Institut Laue Langevin in early 2024. In this paper, we report on recent progress from the Ge cryogenic detector technology, called the CryoCube. More specifically, we present the first demonstration of a 30 eVee (electron equivalent) baseline ionization resolution (RMS) achieved with an early design of the detector assembly and its dedicated High Electron Mobility Transistor (HEMT) based front-end electronics with a total input capacitance of about 40 pF. This represents an order of magnitude improvement over the best ionization resolutions obtained on similar phonon-and-ionization germanium cryogenic detectors from the EDELWEISS and SuperCDMS dark matter experiments, and a factor of three improvement compared to the first fully-cryogenic HEMT-based preamplifier coupled to a CDMS-II germanium detector with a total input capacitance of 250 pF. Additionally, we discuss the implications of these results in the context of the future RICOCHET experiment and its expected background mitigation performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Engineering-In Cybersecurity

Cyber-Informed Engineering is a framework which allows engineers to build resiliency to the impacts of cyber attack into engineered systems starting in the early design phases. This article introduces the framework and provides a description of some of its principles and resources for learning more.

42 ENGINEERING↗
DOE OSTI2023

Perspective of a Dual Energy Electron Storage Ring Cooler for a Hadron Beam Cooling

A dual energy electron storage ring cooler was proposed and explored to maintain a good hadron beam quality against intra-beam scattering and all heating sources in a collider. The unique configuration of this concept is that electron beam in the low energy section extracts heat away from the hadron beam through Coulomb interaction while electron beam in the high energy section releases heat through its intrinsic synchrotron radiation damping. The early design employs a magnetized electron beam for achieving a high cooling efficiency. Recently, a non-magnetized cooling electron beam was explored in this dual energy cooler. It could meet the same cooling requirements while lowering the risks. This paper presents study results on design and optimization of a dual energy storage ring cooler and describes the trade-offs between using magnetized and non-magnetized cooling for this approach.

Lin, Fanglei↗
DOE OSTI2024

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗