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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.

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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Understanding and Predicting the Process of Software Maintenance Releases

One of the major concerns of any maintenance organization is to understand and estimate the cost of maintenance releases of software systems. Planning the next release so as to maximize the increase in functionality and the improvement in quality are vital to successful maintenance management. The objective of this paper is to present the results of a case study in which an incremental approach was used to better understand the effort distribution of releases and build a predictive effort model for software maintenance releases. This study was conducted in the Flight Dynamics Division (FDD) of NASA Goddard Space Flight Center(GSFC). This paper presents three main results: 1) a predictive effort model developed for the FDD's software maintenance release process; 2) measurement-based lessons learned about the maintenance process in the FDD; and 3) a set of lessons learned about the establishment of a measurement-based software maintenance improvement program. In addition, this study provides insights and guidelines for obtaining similar results in other maintenance organizations.

Basili, Victor↗
NASA NTRSDate not supplied

Runway Sign Classifier: A DAL C Certifiable Machine Learning System

In recent years, the remarkable progress of Machine Learning (ML) technologies within the domain of Artificial Intelligence (AI) systems has presented unprecedented opportunities for the aviation industry, paving the way for further advancements in automation, including the potential for single pilot or fully autonomous operation of large commercial airplanes. However, ML technology faces major incompatibilities with existing airborne certification standards, such as ML model traceability and explainability issues or the inadequacy of traditional coverage metrics. Certification of ML-based airborne systems using current standards is problematic due to these challenges. This paper presents a case study of an airborne system utilizing a Deep Neural Network (DNN) for airport sign detection and classification. Building upon our previous work, which demonstrates compliance with Design Assurance Level (DAL) ”D”, we upgrade the system to meet the more stringent requirements of Design Assurance Level ”C”. To achieve DAL C, we employ an established architectural mitigation technique involving two redundant and dissimilar Deep Neural Networks. The application of novel ML-specific data management techniques further enhances this approach. This work is intended to illustrate how the certification challenges of ML-based systems can be addressed for medium criticality airborne applications.

Flight Software↗
DOE OSTI2022

Case Study: WashREIT's Multifamily Solar PV

This case study describes the installation process and resulting payback of rooftop solar PV systems on two multifamily apartment buildings in Washington, D.C. owned by WashREIT.

solar, solar PV, photovoltaic, onsite solar, multi↗
DOE OSTI2022

Resilience with Renewables

This presentation is intended for the DOE Better Buildings Sustainable Corrections Infrastructure Partnership (SCIP) program webinar series. It will explain the INL Resilience Framework, discuss how to apply it for building managers, and give examples of the ways batteries can aid in resilience by walking through a case study conducted for Iowa Lakes Electric Cooperative.

17 WIND ENERGY↗
DOE OSTI2025

Exploring the Potential of ASHRAE Guideline 36 in District Cooling Systems: Preprint

ASHRAE Guideline 36-2021 (G36) provides high-performance control sequences for all-air and hydronic HVAC systems, and it has proven effective at reducing energy use for single building all-air equipment. The most recent version of G36 included control sequences for water-cooled chiller plants, which can be used in district cooling systems (DCSs). Despite not being a traditional application of G36 controls, DCSs could benefit from energy savings that G36 control sequences have demonstrated in single building systems. We therefore investigate the possibility to extend G36 chiller plant control from a single building to district cooling using a real-world district cooling system in Boulder, Colorado as a case study. Four timeframes representing low to peak loads are simulated and analyzed to compare energy use of the district cooling system for three control sequences. Results show that although G36 chiller plant sequences can be applied to DCSs, further analysis and potentially control optimization is needed to ensure energy savings compared to default controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

An ontology to represent synthetic building occupant characteristics and behavior

Since the introduction of the occupant behavior Drivers-Needs-Actions-Systems (DNAS) framework in 2013, researchers have used the framework or further developed it based on their case studies, which include efforts to collect new data on occupant behaviors. The effort is often costly for the relatively few new data points added. Problems emerge when the already collected data do not meet the modelers' interoperability requirements. Previous studies addressed this issue by developing more sophisticated ontologies that enable integration with other datasets and synthetic data methodologies that would meet unique research applications. This paper presents an extension of the DNAS framework for the representation of synthetic occupant data to support various applications and use cases across the building life cycle. An agent-based modeling application is one of our motivations that requires more elaborate characteristics of an occupant-agent or a group-of-agent. The extension, built upon a review of the literature, introduces new elements to the framework that fall into five categories, including socio-economic, geographical location, activities, subjective values, and individual and collective adaptive actions. On-going research includes identifying occupant datasets and developing data fusion methods to generate synthetic occupants, as well as to demonstrate its applications in agent-based modeling coupled with building performance simulation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2014

Behavioral Change and Building Performance: Strategies for Significant, Persistent, and Measurable Institutional Change

The people who use Federal buildings — Federal employees, operations and maintenance staff, and the general public — can significantly impact a building’s environmental performance and the consumption of energy, water, and materials. Many factors influence building occupants’ use of resources (use behaviors) including work process requirements, ability to fulfill agency missions, new and possibly unfamiliar high-efficiency/high-performance building technologies; a lack of understanding, education, and training; inaccessible information or ineffective feedback mechanisms; and cultural norms and institutional rules and requirements, among others. While many strategies have been used to introduce new occupant use behaviors that promote sustainability and reduced resource consumption, few have been verified in the scientific literature or have properly documented case study results. This paper documents validated strategies that have been shown to encourage new use behaviors that can result in significant, persistent, and measureable reductions in resource consumption. From the peer-reviewed literature, the paper identifies relevant strategies for Federal facilities and commercial buildings that focus on the individual, groups of individuals (e.g., work groups), and institutions — their policies, requirements, and culture. The paper documents methods with evidence of success in changing use behaviors and enabling occupants to effectively interact with new technologies/designs. It also provides a case study of the strategies used at a Federal facility — Fort Carson, Colorado. The paper documents gaps in the current literature and approaches, and provides topics for future research.

Wolfe, Amy K.↗
DOE OSTI2020

Nationwide Energy Saving Potential Evaluation for Office Buildings with Occupant-Based Building Controls

The heating ventilation and air-conditioning (HVAC) system is a major contributor to building energy consumption. This paper aims to quantify the nationwide energy savings potential of implementing the occupancy-based control (OBC) for the HVAC system in typical medium-sized office buildings using a whole building simulation program (i.e., EnergyPlus). First, the medium-sized office from the DOE Commercial Prototype Building Models was modified to have detailed layout and space functions. Then, a statistic-algorithm-based tool was used to generate the dynamic occupancy schedules for various rooms. Next, both a baseline case and two OBC cases were created for the comparison based on the updated ASHRAE Standard 90.1 and ASHRAE Guideline 36. The HVAC operation in the baseline case follows a static occupancy schedule and fixed setpoint schedules for both room air temperatures and minimal system outside air flowrates, while the proposed OBC cases use the room temperature reset, system minimum outdoor airflow reset, and zone minimal supply airflow rate reset. These cases were extended to five climate zones in the United States to further quantify the energy savings potential associated with the OBC on a nationwide scale. The preliminary result of this case study shows that there could be significant energy savings potential from the proposed OBC strategies in medium-sized office buildings in the United States.

Pang, Zhihong↗
DOE OSTI2017

An IAEA Initiative to Provide Effective Stakeholder Support Services for International Decommissioning and Environmental Remediation - 17341

The International Atomic Energy Agency (IAEA) has initiated a collaborative effort to promote stakeholder support activities through a stakeholder engagement advisory program (SEAP) as part of Phase II of the Constraints to Implementing Decommissioning and Environmental Remediation (CIDER II) program. CIDER II is a collaborative project involving a broad range of Member States, large and small, with ongoing and/or planned decommissioning and environmental remediation (D and ER) programs. The intent of this sub-group of CIDER II is to facilitate better sharing of information and knowledge in areas of stakeholder communication, engagement and participation, and a framework for directly using stakeholder input in the decision making process. The goal is to support trust building in D and ER decisions for radioactive contamination and facilities. A main premise of the CIDER II program is that stakeholder acceptance is necessary for successful D and ER decisions to be made. This paper introduces some of the major challenges to implementing such a broad scale of support for stakeholder engagement, and approaches to overcoming those challenges. Major challenges include the need to address D and ER decision making in different countries with their different languages, cultures, religions, management structures, and politics. For example, in some cases it might be important strategically to first garner support from upper levels of social, management or political hierarchies, including for example, approaching community leaders, and allowing those leaders to directly address their community. Other sites might have more success, for example, if stakeholder interaction starts with the community members. A specific project strategy also probably depends on who makes the request for stakeholder support services. Once the CIDER II SEAP gains traction, there will be a need to prioritize requests from Member States for assistance in connection with specific D and ER projects. A prioritization tool will be developed based on stakeholder engaged structured decision making (SDM). The projects in which support will initially be focused will span a wide range of D and ER problems, types of stakeholder groups, and technical issues such as potential risk to human health and the environment. A database management system will also be designed to capture information from the different proposed projects and will be expanded to house implemented projects for future reference. The case study database will be an integral part of a web-based system that also contains technical approaches for stakeholder involvement depending on the situational environment. A community of practice will be formed that will involve technical experts in stakeholder engagement and structured decision making, and informed representatives from Member States. This will address the need for SEAP to build capacity and provide education for solving D and ER problems. The web-based system will include technical tools for use by the projects, such as: identification of stakeholder groups; social network analysis (how stakeholders are connected); case study forms; best practice forms; information sheets; and 4tools that will directly support optimization of stakeholder guided solutions to D and ER problems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1990

Overcoming rule-based rigidity and connectionist limitations through massively-parallel case-based reasoning

Symbol manipulation as used in traditional Artificial Intelligence has been criticized by neural net researchers for being excessively inflexible and sequential. On the other hand, the application of neural net techniques to the types of high-level cognitive processing studied in traditional artificial intelligence presents major problems as well. A promising way out of this impasse is to build neural net models that accomplish massively parallel case-based reasoning. Case-based reasoning, which has received much attention recently, is essentially the same as analogy-based reasoning, and avoids many of the problems leveled at traditional artificial intelligence. Further problems are avoided by doing many strands of case-based reasoning in parallel, and by implementing the whole system as a neural net. In addition, such a system provides an approach to some aspects of the problems of noise, uncertainty and novelty in reasoning systems. The current neural net system (Conposit), which performs standard rule-based reasoning, is being modified into a massively parallel case-based reasoning version.

Barnden, John↗
DOE OSTI2016

Efficient Solutions for Existing Homes Case Study: Rehabilitations of USDA Multifamily Homes

Rea Ventures Group, LLC, partnered with Southface Energy Institute (Southface), a member of the U.S. Department of Energy's Partnership for Home Innovation Building America research team, to develop a prescriptive approach for rehabilitating a portfolio of rural multifamily rental properties in Georgia, which was funded by the U.S. Department of Agriculture (USDA).

building america↗
DOE OSTI2023

Carbon Emissions in a Typical New Production Home: A Case Study

This report, prepared by IBACOS, is intended to serve as a foundational document for the residential construction industry to understand how a typical home currently performs relative to building decarbonization goals set for 2030 and 2050. The intent is to help homebuilders benchmark their current performance and better understand the largest sources of carbon emissions in their homes.

Carbon Emissions↗
DOE OSTI2021

Integrated Models for Electrical Distribution Network Planning and District-Scale Building Energy Use

The increase of greenhouse emissions caused by a rise in global energy consumption is pushing the scientific community to develop tools that address key environmental, techno-economic and social issues. One specific area of focus is to create tools that enable the design of high-performance energy districts, including grid-interactive efficient buildings and electrical distribution infrastructure. This paper outlines the approach of integrating a synthetic distribution network tool (RNM-US) with URBANopt™, a modular and customizable software development kit for thermal and electrical modelling of buildings and energy systems at a district scale. First, we describe the algorithms implemented to integrate RNM-US with URBANopt to automatically generate the distribution network for the district considered. Following, we present a case study for the potential uses of the RNM-US integrations with URBANopt, highlighting the capabilities for economic and technical analysis of the distribution network built in relation to the electricity needs of the modelled buildings.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2013

Development of a coupled thermo-hydro-mechanical model in discontinuous media for carbon sequestration

Geomechanical alteration of porous media is generally ignored for most shallow subsurface applications, whereas CO 2 injection, migration, and trapping in deep saline aquifers will be controlled by coupled multifluid flow, energy transfer, and geomechanical processes. The accurate assessment of the risks associated with potential leakage of injected CO 2 and the design of effective injection systems requires that we represent these coupled processes within numerical simulators. The objectives of this study were to develop a coupled thermal-hydro-mechanical model into a single software, and to examine the coupling of thermal, hydrological, and geomechanical processes for simulation of CO 2 injection into the subsurface for carbon sequestration. A numerical model is developed to couple nonisothermal multiphase hydrological and geomechanical processes for prediction of multiple interconnected processes for carbon sequestration in deep saline aquifers. The geomechanics model was based on Rigid Body-Spring Model (RBSM), one of the discrete methods to model discontinuous rock system. Poisson’s effect that was often ignored by RBSM was considered in the model. The simulation of large-scale and long-term coupled processes in carbon capture and storage projects requires large memory and computational performance. Global Array Toolkit was used to build the model to permit the high performance simulations of the coupled processes. The model was used to simulate a case study with several scenarios to demonstrate the impacts of considering coupled processes and Poisson’s effect for the prediction of CO 2 sequestration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Investigating Solutions to Wind Washing Issues in Two-Story Florida Homes, Phase 2

This report provides results from a second-phase research study of a phenomenon generally referred to as wind washing. Wind washing is the movement of unconditioned air around or through building thermal barriers in such a way as to diminish or nullify the intended thermal performance. In some cases, thermal and air barriers are installed very poorly or not at all, and air can readily move from unconditioned attic spaces into quasi-conditioned interstitial spaces. This study focused on the impact of poorly sealed and insulated floor cavities adjacent to attic spaces in Florida homes. In these cases, unconditioned attic air can be transferred into floor cavities through pathways driven by natural factors such as wind, or by thermal differences between the floor cavity and the attic. Air can also be driven into a floor cavity through mechanical forces imposed by return duct leakage in the floor cavity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Investigating Solutions to Wind Washing Issues in Two-Story Florida Homes, Phase 2

With U.S. Department of Energy goals of reducing existing home energy use by 30% and new home energy use by 50%, it is imperative to focus on several energy efficiency measures, including the quality of air and thermal barriers. This report provides results from a second-phase research study of a phenomenon generally referred to as wind washing. Wind washing is the movement of unconditioned air around or through building thermal barriers in such a way as to diminish or nullify the intended thermal performance. In some cases, thermal and air barriers are installed very poorly or not at all, and air can readily move from unconditioned attic spaces into quasi-conditioned interstitial spaces. This study focused on the impact of poorly sealed and insulated floor cavities adjacent to attic spaces in Florida homes. In these cases, unconditioned attic air can be transferred into floor cavities through pathways driven by natural factors such as wind, or by thermal differences between the floor cavity and the attic. Air can also be driven into a floor cavity through mechanical forces imposed by return duct leakage in the floor cavity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Optimal Coordination of Building Loads and Energy Storage for Power Grid and End User Services

Demand response and energy storage play a profound role in the smart grid. The focus of this paper is to evaluate benefits of coordination of flexible loads and energy storage for power grid and end user services. We present a Generalized Battery Model (GBM) to describe the flexibility of building loads and energy storage. A Model Predictive Control (MPC) approach is proposed to characterize the GBM parameters (power and energy limits) for flexible building loads. Moreover, we develop optimal coordination algorithms for them to provide ancillary and end user services such as energy arbitrage, frequency regulation, spinning reserve, as well as energy and demand charge reduction. Several case studies have been performed to demonstrate the efficacy of the GBM and coordination algorithms, and evaluate the benefits of using their flexibility to provide grid and end user services. We show that optimal coordination yields significant cost saving and revenue. Moreover, the best option for grid services is to provide energy arbitrage and frequency regulation, because spinning reserve cannot compete with regulation service. Furthermore, when coordinating flexible loads with energy storage to provide end user services, it is recommended to consider both the time-of-use (TOU) price and demand charge rather than the TOU price only in order to flat the aggregate power profile.

Hao, He↗