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At least 1,423 records · Page 79

Flat conductor cable commercialization project

An undercarpet flat conductor cable and a baseboard flat conductor cable system were studied for commercialization. The undercarpet system is designed for use in office and commercial buildings. It employs a flat power cable, protected by a grounded metal shield, that terminates in receptacles mounted on the floor. It is designed to interface with a flat conductor cable telephone system. The baseboard system consists of a flat power cable mounted in a plastic raceway; both the raceway and the receptacles are mounted on the surface of the baseboard. It is designed primarily for use in residential buildings, particularly for renovation and concrete and masonry construction.

Hogarth, P.↗

An Online Tool for Preliminary Design and Techno-Economic Analysis of District Geothermal Heating and Cooling Systems

District geothermal heating and cooling systems (DGHCS) have significant benefits for reducing energy consumption as well as building- and grid-level peak electric demand. Currently, no publicly available tools are available to effectively design and conduct techno-economic analysis of DGHCS. GeoWISE was originally developed for preliminary design and techno-economic analysis of geothermal heating and cooling systems in an individual commercial or residential building. This paper introduces recent upgrades of GeoWISE that allow users to design and conduct techno-economic analysis of DGHCS. Several new features are implemented in GeoWISE to allow selection and specification of multiple new or existing buildings. A database of information for over 125 million existing U.S. buildings was used in GeoWISE that allows users easily locate existing buildings of interest based on street addresses, and optionally edit information of the buildings (e.g., footprint, vintage, principal functions, number of floors, window-to-wall ratio). Unique energy simulation models of the selected buildings are then automatically created using the Automatic Building Energy Modeling (AutoBEM) and EnergyPlus simulations are performed to predict thermal loads of the buildings. A simplified DGHCS is then designed and simulated to predict its energy use. A central borehole heat exchanger (BHE) of the DGHCS is sized using the RowWise algorithm of GHEDesigner to meet the thermal loads within user-specified land areas for installing BHE. The upgraded GeoWISE reports the needed capacity of heating and cooling equipment in each building, design of the central BHE, energy consumption reduction, and energy cost saving resulting from using DGHCS compared with conventional HVAC systems. A case study is showcased using the upgraded GeoWISE to design and conduct techno-economic analysis of a simplified DGHCS.

Prem Anand Jayaprabha, Jyothis Anand [ORNL] (ORCID↗

Building Artificial Layered Solids from the Bottom-up: Materials by Design to Enable New Energy Technologies

This final technical report summarizes the key accomplishments on this DOE Early Career Program award received by PI Guihua Yu at the University of Texas at Austin. The main goal of this ECP award was to develop synthetic methodologies, self-assembly approaches towards structurally controlled nanosheets-like solids from the bottom up, and to understand and characterize their chemical/physical characteristics for the design of future-generation energy devices with novel functions and properties, that will have direct implications for energy science and technologies such as energy storage and conversion, and catalysis. The project accomplished these goals by completing the following objectives: • Rational design, synthesis, and self-assembly of structurally-controlled molecular ‘nanosheets’ materials. Moving beyond conventional van der Waals two-dimensional crystals, this project enables new synthesis and processing strategies to develop ultrathin nanosheets materials, from inorganic transition-metal oxides-based, to hybrid organic-inorganic nanomaterials, with structural factors such as facet, thickness and pore structure being well controlled during synthesis or assembly processes. • Fundamental understanding and electrochemical characterization of these assembled molecular ‘nanosheets’ materials via charge/mass transport studies through electrochemical intercalation of different metal ions for next-generation energy storage, as well as electrocatalytic studies using this new material platform for understanding catalytic reaction kinetics and the roles of surface functionalization and interface interactions owing to atomic thickness, nanoscale porosity, and other structural factors.

36 MATERIALS SCIENCE↗

Building Operations Efficiencies into NASA's Ares I Crew Launch Vehicle Design

The U.S. Vision for Space Exploration guides the National Aeronautics and Space Administration s (NASA's) challenging missions that expand humanity s boundaries and open new routes to the space frontier. With the Agency's commitment to complete the International Space Station (ISS) and to retire the venerable Space Shuttle by 2010, the NASA Administrator commissioned the Exploration Systems Architecture Study (ESAS) in mid 2005 to analyze options for safe, simple, cost-efficient launch solutions that could deliver human-rated space transportation capabilities in a timely manner within fixed budget guidelines. The Exploration Launch Projects Office, chartered in October 2005, has been conducting systems engineering studies and business planning over the past few months to successively refine the design configurations and better align vehicle concepts with customer and stakeholder requirements, such as significantly reduced life-cycle costs. As the Agency begins the process of replacing the Shuttle with a new generation of spacecraft destined for missions beyond low-Earth orbit to the Moon and Mars, NASA is designing the follow-on crew and cargo launch systems for maximum operational efficiencies. To sustain the long-term exploration of space, it is imperative to reduce the $4.5 billion NASA typically spends on space transportation each year. This paper gives top-level information about how the follow-on Ares I Crew Launch Vehicle (CLV) is being designed for improved safety and reliability, coupled with reduced operations costs.

Dumbacher, Daniel↗

Building Operations Efficiencies into NASA's Ares I Crew Launch Vehicle Design

The U.S. Vision for Space Exploration guides the National Aeronautics and Space Administration's (NASA's) challenging missions that expand humanity's boundaries and open new routes to the space frontier. With the Agency's commitment to complete the International Space Station (ISS) and to retire the venerable Space Shuttle by 2010, the NASA Administrator commissioned the Exploration Systems Architecture Study (ESAS) in 2005 to analyze options for safe, simple, cost-efficient launch solutions that could deliver human-rated space transportation capabilities in a timely manner within fixed budget guidelines. The Exploration Launch Projects (ELP) Office, chartered by the Constellation Program in October 2005, has been conducting systems engineering studies and business planning to successively refine the design configurations and better align vehicle concepts with customer and stakeholder requirements, such as significantly reduced life-cycle costs. As the Agency begins the process of replacing the Shuttle with a new generation of spacecraft destined for missions beyond low-Earth orbit to the Moon and Mars, NASA is designing the follow-on crew and cargo launch systems for maximum operational efficiencies. To sustain the long-term exploration of space, it is imperative to reduce the $4 billion NASA typically spends on space transportation each year. This paper gives toplevel information about how the follow-on Ares I Crew Launch Vehicle (CLV) is being designed for improved safety and reliability, coupled with reduced operations costs. These methods include carefully developing operational requirements; conducting operability design and analysis; using the latest information technology tools to design and simulate the vehicle; and developing a learning culture across the workforce to ensure a smooth transition between Space Shuttle operations and Ares vehicle development.

Dumbacher, Daniel L.↗

Preliminary Design of a Solar Photovoltaic Array for Net-Zero Energy Buildings at NASA Langley

An investigation was conducted to evaluate photovoltaic (solar electric systems) systems for a single building at NASA Langley as a representative case for alternative sustainable power generation. Building 1250 in the Science Directorate is comprised of office and laboratory space, and currently uses approximately 250,000 kW/month of electrical power with a projected use of 200,000 kW/month with additional conservation measures. The installation would be applied towards a goal for having Building 1250 classified as a net-zero energy building as it would produce as much energy as it uses over the course of a year. Based on the facility s electrical demand, a photovoltaic system and associated hardware were characterized to determine the optimal system, and understand the possible impacts from its deployment. The findings of this investigation reveal that the 1.9 MW photovoltaic electrical system provides favorable and robust results. The solar electric system should supply the needed sustainable power solution especially if operation and maintenance of the system will be considered a significant component of the system deployment.

Cole, Stuart K.↗

Lessons learned for composite structures

Lessons learned for composite structures are presented in three technology areas: materials, manufacturing, and design. In addition, future challenges for composite structures are presented. Composite materials have long gestation periods from the developmental stage to fully matured production status. Many examples exist of unsuccessful attempts to accelerate this gestation period. Experience has shown that technology transition of a new material system to fully matured production status is time consuming, involves risk, is expensive and should not be undertaken lightly. The future challenges for composite materials require an intensification of the science based approach to material development, extension of the vendor/customer interaction process to include all engineering disciplines of the end user, reduced material costs because they are a significant factor in overall part cost, and improved batch-to-batch pre-preg physical property control. Historical manufacturing lessons learned are presented using current in-service production structure as examples. Most producibility problems for these structures can be traced to their sequential engineering design. This caused an excessive emphasis on design-to-weight and schedule at the expense of design-to-cost. This resulted in expensive performance originated designs, which required costly tooling and led to non-producible parts. Historically these problems have been allowed to persist throughout the production run. The current/future approach for the production of affordable composite structures mandates concurrent engineering design where equal emphasis is placed on product and process design. Design for simplified assembly is also emphasized, since assembly costs account for a major portion of total airframe costs. The future challenge for composite manufacturing is, therefore, to utilize concurrent engineering in conjunction with automated manufacturing techniques to build affordable composite structures. Composite design experience has shown that significant weight savings have been achieved, outstanding fatigue and corrosion resistance have been demonstrated, and in-service performance has been very successful. Currently no structural design show stoppers exist for composite structures. A major lesson learned is that the full scale static test is the key test for composites, since it is the primary structural 'hot spot' indicator. The major durability issue is supportability of thin skinned structure. Impact damage has been identified as the most significant issue for the damage tolerance control of composite structures. However, delaminations induced during assembly operations have demonstrated a significant nuisance value. The future challenges for composite structures are threefold. Firstly, composite airframe weight fraction should increase to 60 percent. At the same time, the cost of composite structures must be reduced by 50 percent to attain the goal of affordability. To support these challenges it is essential to develop lower cost materials and processes.

Whitehead, R. S.↗

Demographic Information Incorporated Household Energy Consumption Analysis

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗

Metamodels for Computer-Based Engineering Design: Survey and Recommendations

The use of statistical techniques to build approximations of expensive computer analysis codes pervades much of todays engineering design. These statistical approximations, or metamodels, are used to replace the actual expensive computer analyses, facilitating multidisciplinary, multiobjective optimization and concept exploration. In this paper we review several of these techniques including design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning, and kriging. We survey their existing application in engineering design and then address the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes. We conclude with recommendations for the appropriate use of statistical approximation techniques in given situations and how common pitfalls can be avoided.

Simpson, Timothy W.↗

Demographic Information Incorporated Household Energy Consumption Analysis: Preprint

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗

Demographic Information Incorporated Household Energy Consumption Analysis

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗

Exploration of Domain Aware Machine Learning for Grid Analytics: Transfer-Learnt Energy Models to Assist Buildings Control with Sparse Field Data

Buildings are a primary consumer of energy in the United States and are also increasingly being perceived as providers of grid services such as load shifting, shedding and modulation. High fidelity models of building energy consumption are needed to set appropriate baselines for measurement and verification (M&V) of controllers designed for energy efficient operation of buildings and to enable buildings to provide grid services via. participation in demand response programs. State-of-the-art building energy modeling techniques either rely on Physics based models, or extensive instrumentation of the building envelope to gather “big” data to train machine learning based models such as deep neural networks. While Physics based models are often limited by their accuracy, it is not always feasible to gather a significant amount of field data required to train machine learning based models with sufficient accuracy. In this paper, we explore the use of transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality. In particular, we transfer knowledge in the form of data and parameters, from Physics based simulation frameworks to the field to improve the model accuracy, thus resulting in a Physics-informed Machine Learning framework. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that the proposed transfer learning based models provide comparative (and in some cases better) accuracy than state-of-the-art machine learning and deep learning solutions, with just one month of field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ThermoBuild: Online Method Made Available for Accessing NASA Glenn Thermodynamic Data

The new Web site program "ThermoBuild" allows users to easily access and use the NASA Glenn Thermodynamic Database of over 2000 solid, liquid, and gaseous species. A convenient periodic table allows users to "build" the molecules of interest and designate the temperature range over which thermodynamic functions are to be displayed. ThermoBuild also allows users to build custom databases for use with NASA's Chemical Equilibrium with Applications (CEA) program or other programs that require the NASA format for thermodynamic properties. The NASA Glenn Research Center has long been a leader in the compilation and dissemination of up-to-date thermodynamic data, primarily for use with the NASA CEA program, but increasingly for use with other computer programs.

McBride, Bonnie↗

Ares I Avionics Introduction

The Ares I is the next generation human-rated launcher for the United States Constellation program. This system is required to provide single fault tolerance within defined crew safety and mission reliability limits. As part of the effort to achieve those safety goals, Ares I includes an avionics subsystem built as a multistring, voting architecture. The avionics design draws upon experience gained from building fly-by-wire systems for Shuttle, X- 38, and Seawolf. Architectural drivers for the avionics design include using proven technologies with existing suppliers of space rated parts for critical functions (to reduce overall development risk), easing the software development effort by using an off-theshelf, DO-178B certifiable, ARINC-653 operating system in the main flight computers, minimizing mutual data and power connections that might lead to a common-mode hardware failure of the redundant avionics strings, and centralizing overall Ares I command & control within the Upper Stage.

Marchant, Christopher C.↗

Encoding trade-offs and design toolkits in quantum algorithms for discrete optimization: coloring, routing, scheduling, and other problems

Challenging combinatorial optimization problems are ubiquitous in science and engineering. Several quantum methods for optimization have recently been developed, in different settings including both exact and approximate solvers. Addressing this field of research, this manuscript has three distinct purposes. First, we present an intuitive method for synthesizing and analyzing discrete (i.e., integer-based) optimization problems, wherein the problem and corresponding algorithmic primitives are expressed using a discrete quantum intermediate representation (DQIR) that is encoding-independent. This compact representation often allows for more efficient problem compilation, automated analyses of different encoding choices, easier interpretability, more complex runtime procedures, and richer programmability, as compared to previous approaches, which we demonstrate with a number of examples. Second, we perform numerical studies comparing several qubit encodings; the results exhibit a number of preliminary trends that help guide the choice of encoding for a particular set of hardware and a particular problem and algorithm. Our study includes problems related to graph coloring, the traveling salesperson problem, factory/machine scheduling, financial portfolio rebalancing, and integer linear programming. Third, we design low-depth graph-derived partial mixers (GDPMs) up to 16-level quantum variables, demonstrating that compact (binary) encodings are more amenable to QAOA than previously understood. We expect this toolkit of programming abstractions and low-level building blocks to aid in designing quantum algorithms for discrete combinatorial problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Probabilistic Risk Assessment for Concurrent, Conceptual Design of Space Missions

NASA is expanding its capability to perform PRA. This capability gives insight into the links of a suggested design and drives the refinement of the design by identifying optimal areas for investments. Clearly, it is more viable and less expensive to refine a design at the time that it is being conceived. Hence the utility of conducting PRA at the conceptual design phase. Concurrent engineering teams greatly reduce the design time and costs. However, there is currently no standardized means for building probabilistic risk models to assess risks associated with a design produced by such teams. The capability to produce a consistent and valid risk metric associated with such designs would greatly enhance the value of such design teams. This paper explains the experimental results obtained to date from building probabilistic risk models for sample studies conducted at the concurrent engineering design team at the Jet Propulsion Laboratory (TeamX).

conceptual designs↗

Blueprinting extendable nanomaterials with standardized protein blocks

A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight ‘train track’ assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence–structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to ‘back of an envelope’ architectural blueprints.

36 MATERIALS SCIENCE↗