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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 433 records · Page 24

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

SIBatt-3D In-Space/On-Surface 3D Printing of Sodium Ion Batteries using ISRU Materials

Sustainable on-demand power solutions are an absolute necessity as humanity works to establish a permanent presence on the moon and make the journey to Mars. NASA’s SIBatt-3D Early Career Initiative project at MSFC is developing shape-conformable Sodium-Ion batteries that can be 3D printed in-space as needed during extended space missions. SIBatt-3D makes use of the unique advantages of 3D printing to create shape-conformable batteries with improved performance that reduce dead volume in devices and seeks to utilize materials found in Lunar/Martian regolith as feedstocks to provide sustainable power for surface operations on the Moon and Mars. SIBatt-3D’s batteries also have terrestrial implications such as improved battery safety and sustainability.

3D Printing↗

NASA SIBatt-3D: In-Space and On-Surface 3D Printing Sodium-Ion Batteries from ISRU Materials

Sustainable on-demand power solutions are an absolute necessity as humanity works to establish a permanent presence on the moon and make the journey to Mars. NASA’s SIBatt-3D project is developing shape-conformable Sodium-Ion batteries that can be 3D printed in-space as needed during extended space missions. SIBatt-3D seeks to utilize materials found in Lunar/Martian regolith as feedstocks to provide sustainable power for surface operations. SIBatt-3D’s batteries also have terrestrial implications such as improved battery safety and sustainability.

Cameroun Sherrard↗

Extending ISS Life Beyond 2030

The United States On-orbit Segment (USOS) of the International Space Station (ISS) was designed to meet a 15-year on-orbit life. Since the first hardware was launched in late 1998, the ISS would have reached its end of life in 2013. With the realization that the ISS would be needed well into the next decade, and beyond, a multi-disciplinary effort was undertaken to extend the ISS’ life through 2028 and to show that further extension to 2040 and beyond is not only feasible but achievable. Currently, NASA and the ISS international partners have agreed to extend its operations through 2030. This collaborative effort ensures that the ISS will continue to serve as a hub for scientific research, international cooperation, and educational endeavors for the next decade. Maintaining a continuous human presence in Low Earth Orbit (LEO) is desirable for testing new LEO, lunar, and deep-space technologies; conducting scientific research in micro-gravity for the benefit of life on Earth; and enabling a seamless transition of capabilities to one or more commercially owned and operated destinations. This paper provides an overview of the ISS life extension project with a particular focus on the analytical approach used to assess the primary structure. This analytical approach includes future operations planning, critical location screening, on-orbit dynamic load simulation, on-orbit optical property degradation studies, on-orbit thermal analyses, spectra generation, crack model idealization, fracture analyses, and post processing. Structural life results and identification of the most critical on-orbit events are presented. Also addressed are life extension approaches for other affected sub-systems, including: 1. Secondary Structure. 2. Materials. Evaluations consider environmental exposure to atomic oxygen, ionizing and gamma radiation, fluids, etc. Life limited materials, wear, and usage effects are also considered. 3. Environmental Control and Life Support Systems, including oxygen supply and generation, water recovery and management, and regenerative hardware. Evaluations are performed to determine which hardware can be run to failure and which are assessed for life extension. 4. Electrical power system. ISS is powered by eight channels of solar arrays and an electrical energy storage system providing 357 kWh power. Power generation and balance analyses are performed considering hardware degradation and increasing power demand. 5. Logistics and maintenance. Analyses are performed to determine critical spares required to maintain functionality. Consideration is given to supply chain health, obsolescence issues, onboard stowage availability, and up-mass capability. The successful life extension results have built confidence to safely operate, maintain and enhance the ISS well beyond the current decade. Extending the operational life of the ISS maintains an international presence in LEO and serves to avoid a gap in capability necessary to fulfill the exploration and research needs of NASA, international partners, and industry without interruption until a commercial space station is operational.

design life↗

Application of the Software as a Service Model to the Control of Complex Building Systems

In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building. The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analyzed.

25 ENERGY STORAGE↗

Self-Assembly by Instruction: Designing Nanoscale Systems Using DNA-Based Approaches (474th Brookhaven Lecture)

In the field of nanoscience, if you can control how nanoparticles self-assemble in particular structures — joining each other, for example, as molecules can form, atom-by-atom — you can design new materials that have unique properties that industry needs. Nature already uses the DNA genetic code to instruct the building of specific proteins and whole organisms in both plants and people. Taking a cue from nature, scientists at BNL devised a way of using strands of synthetic DNA attached to the surface of nanoparticles to instruct them to self-assemble into specific nanoscale structures, clusters, and three-dimensional organizations. Novel materials designed and fabricated this way promise use in photovoltaics, energy storage, catalysis, cell-targeted systems for more effective medical treatments, and biomolecular sensing for environmental monitoring and medical applications. To find out more about the rapid evolution of this nanoassembly method and its applications, join Physicist Oleg Gang of the Center for Functional Nanomaterials (CFN) as he gives the 474th Brookhaven Lecture, titled “Self-Assembly by Instruction: Designing Nanoscale Systems Using DNA-Based Approaches." Gang, who has led this work at the CFN, will explain the rapid evolution of this nanoassembly method, and discuss its present and future applications in highly specific biosensors, optically active nano-materials, and new ways to fabricate complex architectures in a rational manner via self-assembly. Gang and his colleagues used the CFN and the National Synchrotron Light Source (NSLS) facilities to perform their groundbreaking research. At the CFN, the scientists used electron microscopes and optical methods to visualize the clusters that they fabricated. At the NSLS, they applied x-rays to study a particles-assembly process in solution, DNA’s natural environment. Gang earned a Ph.D. in soft matter physics from Bar-Ilan University in 2000, and he was a Rothschild Fellow at Harvard University from 1999 to 2002. After joining BNL as a Goldhaber Fellow in 2002, he became an assistant scientist at the CFN in 2004. He became the CFN’s leader for Soft and Biological Nanomaterials Theme Group in 2006, and earned the title of scientist in 2009. Gang has received numerous honors and recognitions, including the 2010 Gordon Battelle Prize for Scientific Discovery.

36 MATERIALS SCIENCE↗

Application of the Software as a Service Model to the Control of Complex Building Systems

In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building. The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analysed.

25 ENERGY STORAGE↗

Using an operator training simulator in the undergraduate chemical engineering curriculim

An operator training simulator (OTS) is to the chemical engineer what a flight simulator is to the aerospace engineer. The basis of an OTS is a high-fidelity dynamic model of a chemical process that allows an engineer to simulate start-up, shut-down, and normal operation. It can also be used to test the skill and ability of an engineer or operator to respond and control some unforeseen situation(s) through the use of programmed malfunctions. West Virginia University (WVU) is a member of the National Energy Technology Laboratory’s Regional University Alliance (NETL-RUA). Working through the NETL-RUA, the authors have spent the last four years collaborating on the development of a high-fidelity OTS for an Integrated Gasification Combined Cycle (IGCC) power plant with CO{sub 2} capture that is the cornerstone of the AVESTARTM (Advanced Virtual Energy Simulation Training And Research) Center with sister facilities at NETL and WVU in Morgantown, WV. This OTS is capable of real-time dynamic simulation of IGCC plant operation, including start-up, shut-down, and power demand load following. The dynamic simulator and its human machine interfaces (HMIs) are based on the DYNSIM and InTouch software, respectively, from Invensys Operations Management. The purpose of this presentation is to discuss the authors’ experiences in using this sophisticated dynamic simulation-based OTS as a hands-on teaching tool in the undergraduate chemical engineering curriculum. At present, the OTS has been used in two separate courses: a new process simulation course and a traditional process control course. In the process simulation course, concepts of steady-state and dynamic simulations were covered prior to exposing the students to the OTS. Moreover, digital logic and the concept of equipment requiring one or more permissive states to be enabled prior to successful operation were also covered. Students were briefed about start-up procedures and the importance of following a predetermined sequence of actions in order to start-up the plant successfully. Student experience with the dynamic simulator consisted of a six-hour training session in which the Claus sulfur capture unit of the IGCC plant was started up. The students were able to operate the simulator through the InTouch-based HMI displays and study and understand the underlying dynamic modeling approach used in the DYNSIM-based simulator. The concepts learned during the training sessions were further reinforced when students developed their own DYNSIM models for a chemical process and wrote a detailed start-up procedure. In the process control course, students learned how the plant responds dynamically to changes in the manipulated inputs, as well as how the control system impacts plant performance, stability, robustness and disturbance rejection characteristics. The OTS provided the opportunity to study the dynamics of complicated, “real-life” process plants consisting of hundreds of pieces of equipment. Students implemented ideal forcing functions, tracked the time-delay through the entire plant, studied the response of open-loop unstable systems, and learned “good practices” in control system design by taking into account the real-world events where significant deviations from the “ideal” or “expected” response can occur. The theory of closed-loop stability was reinforced by implementing limiting proportional gain for stability limits of real plants. Finally, students were divided into several groups where each group was tasked to control a section of the plant within a set of operating limits in the face of disturbances and simulated process faults. At the end of this test, they suggested ways to improve the control system performance based on the theory they learned in class and the hands-on experience they earned while working on the OTS.

97 MATHEMATICS AND COMPUTING↗

System and method of cylinder deactivation for optimal engine torque-speed map operation

This disclosure provides a system and method for determining cylinder deactivation in a vehicle engine to optimize fuel consumption while providing the desired or demanded power. In one aspect, data indicative of terrain variation is utilized in determining a vehicle target operating state. An optimal active cylinder distribution and corresponding fueling is determined from a recommendation from a supervisory agent monitoring the operating state of the vehicle of a subset of the total number of cylinders, and a determination as to which number of cylinders provides the optimal fuel consumption. Once the optimal cylinder number is determined, a transmission gear shift recommendation is provided in view of the determined active cylinder distribution and target operating state.

33 ADVANCED PROPULSION SYSTEMS↗

Thermosyphon Cooler Hybrid System for Water Savings in an Energy-Efficient HPC Data Center: Modeling and Installation: Preprint

The Thermosyphon Cooler Hybrid System (TCHS) integrates the control of a dry heat rejection device, the thermosyphon cooler (TSC), with an open cooling tower. A combination of equipment and controls, this new heat rejection system embraces the 'smart use of water,' using evaporative cooling when it is most advantageous and then saving water and modulating toward increased dry sensible cooling as system operations and ambient weather conditions permit. Innovative fan control strategies ensure the most economical balance between water savings and parasitic fan energy. The unique low-pressure-drop design of the TSC allows water to be cooled directly by the TSC evaporator without risk of bursting tubes in subfreezing ambient conditions. Johnson Controls partnered with the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories to deploy the TSC as a test bed at NREL's high-performance computing (HPC) data center in the first half of 2016. Located in NREL's Energy Systems Integration Facility (ESIF), this HPC data center has achieved an annualized average power usage effectiveness rating of 1.06 or better since 2012. Warm-water liquid cooling is used to capture heat generated by computer systems direct to water; that waste heat is either reused as the primary heat source in the ESIF building or rejected using evaporative cooling. This data center is the single largest source of water and power demand on the NREL campus, using about 7,600 m3 (2.0 million gal) of water during the past year with an hourly average IT load of nearly 1 MW (3.4 million Btu/h) -- so dramatically reducing water use while continuing efficient data center operations is of significant interest. Because Sandia's climate is similar to NREL's, this new heat rejection system being deployed at NREL has gained interest at Sandia. Sandia's data centers utilize an hourly average of 8.5 MW (29 million Btu/h) and are also one of the largest consumers of water on Sandia's site. In addition to describing the installation of the TSC and its integration into the ESIF, this paper focuses on the full heat rejection system simulation program used for hourly analysis of the energy and water consumption of the complete system under varying operating scenarios. A follow-up paper will detail the test results. The evaluation of the TSC's performance at NREL will also determine a path forward at Sandia for possible deployment in a large-scale system not only for data center use but also possibly site wide.

97 MATHEMATICS AND COMPUTING↗

Load Factor and Unserved Energy Webinar

This presentation consists of slides from a webinar given on October 25, 2019. The slides give an overview of load factor forecasting and how it can be incorporated into energy and power demand forecasts, with a special eye towards accounting for unserved energy. It includes case studies from other countries, highlighting how load factor is used in their individual load forecasts. The slides then review and compare various load forecasts for Pakistan's electricity grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

LWR Aging Management for Life Beyond 80

While several decades of materials degradation research enabled the current US fleet of Light Water Reactors (LWR) to plan to produce electrical power through extended operations up to 80 years of plant life, it now seems appropriate to evaluate what issues, methods, and timelines need to be considered to meet the expected electric power demands for life beyond eighty (LBE) years. To address these questions, it will be necessary to review the electrical capacity and the projected LWR fleet capacity including new builds and advanced reactors. This effort should begin with a materials degradation assessment focused on known and possible unknown issues using a reduced Expanded Materials Degradation Assessment [1], which was employed to identify knowledge gaps for a second license renewal (60-80 yrs.). The focus of the LBE assessment should include: Establishing a timeline to initiate assessments of possible materials aging issues and to ensure sufficient time to evaluate materials degradation research gaps; assessing components and materials to be evaluated, e.g., metals (reactor pressure vessels and alloys within and outside the pressure boundary), concrete, cables, as well as mitigation methods, advanced monitoring, and validation with ex-service materials; initiating a LBE research plan focused on developing an expanded mechanistic understanding of materials degradation and refined models through Codes and Standards evaluation for use by the nuclear industry; and maintaining and strengthening the nuclear materials human knowledge base to address new and as yet unknown degradation modes.

Chen, Xiang↗

Advancing Federal Infrastructure Through Innovation: Selecting Electric Vehicle Charging Infrastructure Wisely

The Biden Administration's issuance of Executive Orders directly addressing and accelerating Federal fleet electrification places an onus on both fleet and facility managers. This panel will help fleet and facility personnel understand how to select EVSE infrastructure in terms of implementation, energy management, and costs of procurement, installation/deployment, and electricity. The panel will cover technology aspects to include managed EVSE, bi-directional charging, implications on local electrical systems and storage needs in certain cases to buffer power demand. Discussion will include various considerations relevant to ensuring adequate EVSE, balancing infrastructure needs, and upgrades with fleet needs. The panelists will discuss how to provide sufficient infrastructure support, including which stakeholders to involve, procurement impediments, easement locations, and requirements that arise during the design and implementation process.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Final CRADA Report: Accelerated Burn-up Accumulation Test of Clean Core Thorium Energy Designated ANEEL Fuel

Clean Core Thorium Energy (CCTE), LLC, located in Oak Brook, Illinois, is committed to the development of alternative nuclear fuels. CCTE is focused on leveraging the inherent benefits of thorium to create a novel nuclear fuel solution for our worlds growing power demand. Unlike some other fuel cycles proposing to use thorium in advanced reactors, CCTE is focused on deploying solid fuel designs (ceramic pellets in metallic cladding) in existing pressurized heavy-water reactors (PHWRs) and Canada deuterium uranium (CANDU) reactors. CCTE’s fuel design, referred to as Advanced Nuclear Energy for Enriched Life (ANEEL), uses mixed thorium-uranium oxide ((Th,U)O2) to enhance reactor operational strategies while producing significantly low attractiveness material in terms of nuclear proliferation. The overall project objective is to investigate the performance of high burnup ANEEL fuel via an irradiation experiment to be performed in the Advanced Test Reactor (ATR) at the Idaho National Laboratory (INL). The scope of work for this CRADA was specifically aimed at performing conceptual design and analysis to support development of an irradiation test rig, development of a fuel fabrication process for the experiment pellets, fabrication and qualification of the pellets, and shipment of the pellets to INL so they can be used to construct experiment rodlets.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Event-Based Energy Impact Tracking and Forecasting with Limited Measurements for Rooftop Units

Packaged air conditioning units and heat pumps, also known as rooftop units (RTUs), are responsible for almost 133 billion kWh of electricity usage annually on site for space cooling U.S. commercial buildings. In addition, the use of heat pumps is a trend we expect to accelerate as buildings transition from fossil fuel-based heating to electricity as a key step for decarbonizing the U.S. commercial buildings sector. However, the operation conditions and energy use of RTUs and heat pumps are usually not well monitored as they are not commonly integrated with building automation systems and lack exposed sensing and control points. To fill this gap, this paper proposes a framework for tracking and forecasting energy impacts resulting from degradation of performance and improved performance for unit servicing using limited data. The proposed framework makes use of a constrained dataset, specifically measurements of the outdoor air temperature and the power demand of individual RTUs, to track and forecast changes in energy use associated with changes in performance over various temporal horizons ranging from days to weeks. Following the detection of an RTU fault, performance degradation, or performance improvement, the framework employs a prediction model to assess the cumulative energy impact. We demonstrate the effectiveness of the method with field-collected data for servicing and degradation examples and compare the predicting accuracy of Gradient Boosting Decision Tree (GBDT) Regression models to Support Vector Regression and Linear Regression models. The results show that GBDT achieved the best accuracy for time-series validation datasets for the servicing and degradation cases, and the prediction model was able to track the cumulative energy impacts of events. The proposed framework can inform building owners of the cumulative change in energy usage of RTUs associated with performance degradation, performance improvement, or a fault.

packaged air conditioners, packaged heat pumps, ro↗

Evaluating demand response opportunities for power systems resilience using MILP and MINLP Formulations

While peak shaving is commonly used to reduce power costs, chemical process facilities that can reduce power consumption on demand during emergencies (e.g., extreme weather events) bring additional value through improved resilience. For process facilities to effectively negotiate demand response (DR) contracts and make investment decisions regarding flexibility, they need to quantify their additional value to the grid. We present a grid–centric mixed–integer stochastic programming framework to determine the value of DR for improving grid resilience in place of capital investments that can be cost prohibitive for system operators. We formulate problems using both a linear approximation and a nonlinear alternating current power flow model. Our numerical results with both models demonstrate that DR can be used to reduce the capital investment necessary for resilience, increasing the value that chemical process facilities bring through DR. Furthermore, the linearized model often underestimates the amount of DR needed in our case studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development and Demonstration of Medium-Heavy Duty PHEV Work Trucks

The heavy-duty vehicle market (Class 6-8) has been a difficult segment for the introduction of plug-in vehicles due to the large energy storage requirement (with corresponding cost), challenging duty cycles, and the diversity of vehicle configurations. The Work Truck market represents a significant opportunity for Heavy-Duty PHEV adoption. (1) The usage cycle includes driving and stationary/worksite power requirements, ensuring full daily usage of the grid-charged battery (battery size: 15-30kWhr). Though daily driving can often be short (an average of 26 miles per day), worksite power includes substantial demand (hydraulics, exportable 110/220V power, 12V support, HVAC). (2) Worksite power demands for conventional vehicles require continuous loaded engine operation, resulting in significant emissions, fuel consumption and noise impacts. (3) These trucks serve an industry that is highly diverse in final vehicle duty cycle, configuration, and jobsite power demands resulting in the need for a modular, configurable hybrid solution. Through this program, Odyne has developed and demonstrated a medium/heavy duty plug-in hybrid solution capable of meeting the needs of the work truck market while delivering fuel and emissions reductions of 50% or greater when evaluated against the full-day work truck duty cycle. The Odyne system developed in this project was released for commercial sale as the G2V7 Odyne Plug-in Hybrid and ePTO systems. The testing and field demonstration proved that the Odyne hybrid system is capable of reducing work truck fuel use and emissions by over 50% while subsequent commercial sales demonstrate the flexibility of the modular design and the capability to support electric systems of 12 – 30 kW and hydraulic based systems of 60 kW (80 HP) or greater. Odyne is continuing to work with suppliers on reducing component costs and working with supporting agencies to initiate projects to increase the driving and full day fuel and emissions savings in order to continue to improve the customer value and return on investment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗