Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “building case study”

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 1,009 records · Page 56

Acoustic Bubble Removal from Boiling Surfaces

The object of the study was the investigation of the forces generated by standing acoustic waves on vapor bubbles, both far and near boundaries. In order to accomplish this objective, in view of the scarcity of publications on the topic, it has been necessary to build an edifice of knowledge about vapor bubbles in sound and flow fields from the ground up, as it were. We have addressed problems of gradually greater difficulty as follows: 1. In the first place, the physics of an stationary isolated bubble subject to a sound field in an unbounded liquid was addressed; 2. The case of bubbles translating in a stationary pressure field was then considered; 3. This was followed by a study of the combined effects of sound and translation, 4. And of a neighboring boundary 5. Finally, a new method to deal with nonspherical bubbles was developed- In addition to the work on vapor bubbles, some studies on gas bubbles were conducted in view of NASA's interest in the phenomenon of sonoluminescence.

Prosperetti, Andrea↗

Chapter 6: Abuse Response of Batteries Subjected to Mechanical Impact

Electrochemical and thermal models to simulate nominal performance and abuse response of lithium-ion cells and batteries have been reported widely in the literature. Studies on mechanical failure of cell components and how such events interact with the electrochemical and thermal response are relatively less common. This chapter outlines a framework developed under the Computer Aided Engineering for Batteries program to couple failure modes resulting from external mechanical loading to the onset and propagation of electrochemical and thermal events that follow. Starting with a scalable approach to implement failure criteria based on thermal, mechanical, and electrochemical thresholds, we highlight the practical importance of these models using case studies at the cell and module level. The chapter also highlights a few gaps in our understanding of the comprehensive response of batteries subjected to mechanical crash events, the stochastic nature of some of these failure events, and our approach to build safety maps that help improve robustness of battery design by capturing the sensitivity of some key design parameters to heat generation rates under different mitigation strategies.

abuse simulations↗

A Topology Optimization Framework to Facilitate Adoption of Advanced District Thermal Energy Systems

Advanced district thermal energy systems, which circulate water at temperatures near ambient conditions, and facilitate the utilization of waste heat and renewable thermal sources, can lower the carbon-intensity of urban districts, advancing the U.N. Sustainable Development Goals. Optimization of the network topology — the selection of the best subset of buildings and the best network to connect them, to minimize life cycle cost — can increase adoption of these system in appropriate applications. The potential "solution space" of the topology optimization problem grows factorially with the number of buildings in the district, motivating the consideration of a design heuristic. In this study, a heuristic for the network selection was evaluated with an exhaustive search, for a prototypical four-building district. For the prototypical district considered, the heuristic was effective in selecting an optimal network topology. Additionally, it was found that, in this case, the selection of the subset of buildings was more influential on the life cycle cost than the selection of the network topology. This work is part of a larger effort to develop a topology optimization framework for district thermal energy systems, which is anticipated to address barriers to adoption of ambient-temperature systems.

28 EE - Advanced Manufacturing Office (EE-5A)↗

Energy, Exergy, and Emission Analysis on Industrial Air Compressors

Abstract Air compressors, a key fluid power technology, play an essential role in industrial plants and office buildings, hospitals, and other types of facilities. The efficient use of the air compressor is crucial. By controlling unnecessary inefficiencies, high energy consumption can be reduced. This study aims to provide energy and exergy analysis on air compressors for different industries. Detailed case studies were also analyzed. The case study focuses on the energy and exergy analyses of the compressed air system of foundry industries. The results indicate that applying the six improvement recommendations yields significant amounts of energy and cost savings and significant improvements in the system's overall performance. The payback periods for different recommendations are economically feasible and worthwhile to use. The suggested improvement methods can provide cost savings with a low payback period.

Energy & Fuels↗

Insights into Methodologies and Stochastic Optimization of Thermal Energy Storage-Coupled Advanced Reactor Systems: A Comparison of Methods for Accessing Long-Term Sub-System Sizing Adequacy

This paper investigates the potential of coupling Thermal Energy Storage (TES) with Advanced Reactors (ARs) to address uncertainties posed by climate change in deep decarbonized power systems. The TES Use-case Team at Idaho National Laboratory (INL) has examined the potential of storing thermal energy from ARs during low demand periods and optimizing discharge during peak-priced hours, in both steady-state and transient conditions. Building on this groundwork, this study bridges the gaps in optimal sizing of the sub-system of TES-coupled AR systems using Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON), INL?s framework for grid optimization. By applying this framework, we present statistically-robust optimal charge, discharge including balance of plant (BOP), and storage sizing for the High-Temperature Gas-Cooled Reactor (HTGR) with 203 MWth output. To this end, we generated synthetic price samples for 30 years using 2018 ? 2021 real-time market data from ERCOT, PJM and MISO. Our results reveals that the TES-coupled HTGR system is highly effective in maximizing revenue from electricity sales. We observed a substantial increase of 40 % in ERCOT and a noteworthy 15 % increase in PJM and MISO when compared to the conventional BOP without TES. This improvement is achieved through regionally-tailored sub-system sizing, which ranges from 398 to 416 MWth for the discharge system and 610 to 1029 MWth for the TES. We find that the average electricity price directly impacts the overall economics, while price volatility influences storage size. Additional sensitivity analyses were performed to access the impact of key assumptions on system economics and sizing, differentiating the optimization window (i.e., 24 ? 219 hours of chronological observations) and by imposing storage continuity condition in tracking TES cycles. We observed that at the 120-hour of the optimization window, a reasonable balance between computation time and accuracy was achieved. Our analysis also highlights the significance of conducting multi-day cycle analysis (> 120-hour) for TES to capture interaction between electricity prices and storage dynamics, providing a comprehensive understanding of TES behavior that AR developers should integrate into their plant designs.

25 ENERGY STORAGE↗

Recruiting and Retaining Talent within the Global Waste Management and Decommissioning Industry - 17192

Every organisation or project can be defined as the people within it. The difference between having the right people with a culture of loyalty and the wrong people with a culture of high staff turnover is huge. Therefore, the way that the global waste management and decommissioning industry approaches recruitment and retention is a critical success factor. My colleagues and I have been fortunate enough to support organisations in the nuclear industry across more than 30 countries in recruiting and retaining talented professionals with rare skills. This experience has given us a unique first hand insight, and answers for questions including the following: - What attracts graduates and experienced professionals to choose a career in the nuclear industry: in waste management, in operations or in new build? - How can we leverage this knowledge to attract more talented individuals to work in the nuclear industry, and in waste management and decommissioning in particular? - How can organisations access the existing global talent pool within waste management and decommissioning? (including case studies of best practice in global recruiting); - What innovative methods are organisations using to successfully find talent? (methods such as strategic secondments, partnerships and knowledge transfer initiatives); - Why do people typically leave an organization or project in the waste management and decommissioning industry? - What examples of best practice and lessons learned exist that can help us understand and increase staff retention in the waste management and decommissioning industry? This paper will answer the questions above and provide recent and relevant examples to substantiate key observations. The objectives of the presentation are: - To give the audience a summary of best practice and lessons learned related to recruitment and retention in the global waste management and decommissioning industry, and also in the wider nuclear industry; - To show the benefits of taking a global view when looking for talent and explaining how to access the global talent pool; - To provide an insight in to what motivates talented people to join the industry and conversely what de-motivates them and causes them to leave; - To provide information about how organisations in the waste management and decommissioning industry can play to their strengths and better compete with other industries that are recruiting for the same talent; - To provide useful and practical actions that will add value to the audience and their organisations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

New Whole-House Solutions Case Study: Quadrant Homes

Quadrant moved ducts and high efficiency furnace inside conditioned space on nearly all 300 customizable house plans. The builder uses dry, true factory-assembled walls, extensive air sealing, and just in time delivery for pre-sold homes.

air sealing↗

Functional Characterization of Four Putative δ1-Pyrroline-5-Carboxylate Reductases from Bacillus subtilis

In most living organisms, the amino acid proline is synthesized starting from both glutamate and ornithine. In prokaryotes, in the absence of an ornithine cyclodeaminase that has been identified to date only in a small number of soil and plant bacteria, these pathways share the last step, the reduction of δ1-pyrroline-5-carboxylate (P5C) catalyzed by P5C reductase (EC 1.5.1.2). In several species, multiple forms of P5C reductase have been reported, possibly reflecting the dual function of proline. Aside from its common role as a building block of proteins, proline is indeed also involved in the cellular response to osmotic and oxidative stress conditions. Genome analysis of Bacillus subtilis identifies the presence of four genes (ProH, ProI, ProG, and ComER) that, based on bioinformatic and phylogenic studies, were defined as respectively coding a putative P5C reductase. Here we describe the cloning, heterologous expression, functional analysis and small-angle X-ray scattering studies of the four affinity-purified proteins. Results showed that two of them, namely ProI and ComER, lost their catalytic efficiency or underwent subfunctionalization. In the case of ComER, this could be likely explained by the loss of the ability to form a dimer, which has been previously shown to be an essential structural feature of the catalytically active P5C reductase. The properties of the two active enzymes are consistent with a constitutive role for ProG, and suggest that ProH expression may be beneficial to satisfy an increased need for proline.

59 BASIC BIOLOGICAL SCIENCES↗

Building a functional, integrated GIS/remote sensing resource analysis and planning system

To be an effective tool for resource analysis and planning, a geographic information system (GIS) needs to be integrated with a digital remote sensing capability. To be truly functional, the paired system must be driven by grass roots local needs. A case study couched in a Soil Conservation District in northern Utah is presented. Agency representatives determined that the most fundamental data sets to be entered into the GIS system analysis system in the first round were: land use/land cover; geomorphic/soil unit data; hydrologic unit data; and digital terrain. The least expensive and best ways to obtain these data were determined. Data were acquired and formatted to enter the state's PRIME/ARC-INFO GIS, and are being interrogated for resource management decisions related to such issues as agricultural preservation, urban expansion, soil erosion control, and dam siting.

Ridd, M. K.↗

A novel probabilistic regression model for electrical peak demand estimate of commercial and manufacturing buildings

Due to the high cost of electricity in commercial and industrial sectors, demand forecast models have gained increasing attention. However, there are two unresolved issues: (1) Models are not adaptable when exposed to previously unknown data (2) The value of regression methods vs. state-of-the-art machine learning models has not been made apparent before. This study’s goal is to develop probabilistic demand estimation models. Herein, we propose a probabilistic Bayesian regression framework that can not only estimate future demands with high accuracy but also be updated once new information is available. By applying the proposed algorithm to two real-world case studies (commercial and manufacturing), we show a 40.3% and 30.8% improvement in terms of mean absolute error for the two cases. Moreover, the proposed technique outperforms powerful machine learning approaches, including support vector machine by 10.39%, random forest by 6.17%, and multilayer perceptron by 9.14% in terms of mean absolute percentage error.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗