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At least 73 records · Page 4

Thin-film ferroelectric materials and their applications

Ferroelectric materials, because of their robust spontaneous electrical polarization, are widely used in various applications. Recent advances in modelling, synthesis and characterization techniques are spurring unprecedented advances in the study of these materials. In this Review, we focus on thin-film ferroelectric materials and, in particular, on the possibility of controlling their properties through the application of strain engineering in conventional and unconventional ways. We explore how the study of ferroelectric materials has expanded our understanding of fundamental effects, enabled the discovery of novel phases and physics, and allowed unprecedented control of materials properties. We discuss several exciting possibilities for the development of new devices, including those in electronic, thermal and photovoltaic applications, and transduction sensors and actuators. We conclude with a brief survey of the different directions that the field may expand to over the coming years.

36 MATERIALS SCIENCE↗

Darshan for HEP applications

Modern HEP workflows must manage increasingly large and complex data collections. HPC facilities may be employed to help meet these workflows’ growing data processing needs. However, a better understanding of the I/O patterns and underlying bottlenecks of these workflows is necessary to meet the performance expectations of HPC systems.Darshan is a lightweight I/O characterization tool that captures concise views of HPC application I/O behavior. It intercepts application I/O calls at runtime, records file access statistics for each process, and generates log files detailing application I/O access patterns.Typical HEP workflows include event generation, detector simulation, event reconstruction, and subsequent analysis stages. A study of the I/O behavior of the ATLAS simulation and filtering stage, and the CMS simulation workflow using Darshan is presented, including insights into the I/O operations and data access size.

Wang, Rui↗

Evaluating Online Global Recovery with Fenix Using Application-Aware In-Memory Checkpointing Techniques

Exascale systems promise the potential for computation at unprecedented scales and resolutions, but achieving exascale by the end of this decade presents significant challenges. A key challenge is due to the very large number of cores and components and the resulting mean time between failures (MTBF) in the order of hours or minutes. Since the typical run times of target scientific applications are longer than this MTBF, fault tolerance techniques will be essential. An important class of failures that must be addressed is process or node failures. While checkpoint/restart (C/R) is currently the most widely accepted technique for addressing processor failures, coordinated, stable-storage-based global C/R might be unfeasible at exascale when the time to checkpoint exceeds the expected MTBF. This paper explores transparent recovery via implicitly coordinated, diskless, application-driven checkpointing as a way to tolerate process failures in MPI applications at exascale. The discussed approach leverages User Level Failure Mitigation (ULFM), which is being proposed as an MPI extension to allow applications to create policies for tolerating process failures. Specifically, this paper demonstrates how different implementations of application-driven in-memory checkpoint storage and recovery compare in terms of performance and scalability. We also experimentally evaluate the effectiveness and scalability of the Fenix online global recovery framework on a production system -the Titan Cray XK7 at ORNL- and demonstrate the ability of Fenix to tolerate dynamically injected failures using the execution of four benchmarks and mini-applications with different behaviors.

97 MATHEMATICS AND COMPUTING↗

Fuel Cell Backup Power System for Grid-Service and Micro-Grid in Telecommunication Applications

This paper presents the feasibility and economics of using fuel cell backup power systems in telecommunication cell towers to provide grid services (e.g., ancillary services, demand response). The fuel cells are able to provide power for the cell tower during emergency conditions. This study evaluates the strategic integration of clean, efficient, and reliable fuel cell systems with the grid for improved economic benefits. The backup systems have potential as enhanced capability through information exchanges with the power grid to add value as grid services that depend on location and time. The economic analysis has been focused on the potential revenue for distributed telecommunications fuel cell backup units to provide value-added power supply. This paper shows case studies on current fuel cell backup power locations and regional grid service programs. The grid service benefits and system configurations for different operation modes provide opportunities for expanding backup fuel cell applications responsive to grid needs. The objective of this work primarily focuses on how fuel cells can become a significant part of the telecom backup power to reduce system costs, environmental impact, and dependence on fossil fuels, while ensuring continuity of indispensable service for mobile users. The study identifies the approaches on the fuel cell application through nano/microgrids for an extensive network of fuel cells as distributed energy resources. The possibilities of various application scenarios extend the fuel cell technologies and microgrid for reliable power supply.

30 DIRECT ENERGY CONVERSION↗

TU-AB-201-01: A Comprehensive Planning Comparison Study Between a Novel Direction Modulated Brachytherapy Tandem Applicator and Conventional T&R Applicator for Image Guided Cervical Cancer Brachytherapy

Purpose: To demonstrate that utilization of a novel, intensity modulation capable, direction modulated brachytherapy (DMBT) tandem applicator can improve plan quality compared with conventional T&R applicator during an image guided cervical cancer brachytherapy. Methods: 45 cervical cancer patients treated with PDR brachytherapy were reviewed. Of them, a) 27 were treated using T&R only, b) 9 were treated using T&R with needles attached to the ring, and c) the remaining 9 were treated using T&R with needles attached to the ring (AN) as well as additional free-hand-loaded needles (FN). The DMBT tandem design has 6 peripheral holes of 1.3-mm diameter, grooved along a nonmagnetic tungsten alloy rod, enclosed in a plastic sheath with total 6.0-mm diameter. An in-house-coded inverse planning system was used for planning DMBT and T&R cases. All typical clinical constraints including OAR dose limits, dwell times, and loading patterns were respected. For the DMBT and T&R applicators, the plans were optimized with the same conventional ring in place, but repeatedly planned with and without AN/FN needles. All generated plans were normalized to the same D90 of the clinically treated plans. Results: For the plans in category a), DMBT generally outperformed T&R with average reduction in D2cc of −2.39%, −5.21%, and −2.69% for bladder, rectum, and sigmoid, respectively. For the plans in category b) and c), DMBT generally outperformed T&R if the same needles in AN/FN were utilized in both cases with average reduction in D2cc of −1.82%, −3.40%, and −6.04%, respectively. For the cases where the needles were not utilized for both applicators, an average D2cc reduction of −7.45%, −7.61%, and 17.47% were observed, respectively. Conclusions: Under the same clinical conditions, with/without needles, the DMBT applicator tends to generate more favorable plans compared with the conventional T&R applicator, and hence, is a promising technology.

60 APPLIED LIFE SCIENCES↗

Management of Risks Associated with Application of Novel Materials in Novel Operating Environments in Novel Reactor Designs

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. These challenges are discussed in the paper, and a potentially applicable modeling approach based on cumulative damage rather than failure rates is briefly illustrated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Application of Smart Solid State Sensor Technology in Aerospace Applications

Aerospace applications require a range of chemical sensing technologies to monitor conditions in both space vehicles and aircraft operations. One example is the monitoring of oxygen. For example, monitoring of ambient oxygen (O2) levels is critical to ensuring the health, safety, and performance of humans living and working in space. Oxygen sensors can also be incorporated in detection systems to determine if hazardous leaks are occurring in space propulsion systems and storage facilities. In aeronautic applications, O2 detection has been investigated for fuel tank monitoring. However, as noted elsewhere, O2 is not the only species of interest in aerospace applications with a wide range of species of interest being relevant to understand an environmental or vehicle condition. These include combustion products such as CO, HF, HCN, and HCl, which are related to both the presence of a fire and monitoring of post-fire clean-up operations. This paper discusses the development of an electrochemical cell platform based on a polymer electrolyte, NAFION, and a three-electrode configuration. The approach has been to mature this basic platform for a range of applications and to test this system, combined with "Lick and Stick" electronics, for its viability to monitor an environment related to astronaut crew health and safety applications with an understanding that a broad range of applications can be addressed with a core technology.

Hunter, Gary W.↗

An optimization-based web application for synthesis and analysis of biomass-to-fuel strategies: An optimization-based web application for synthesis and analysis of biomass-to-fuel strategies

We develop an optimization-based web application for assessing biomass-to-fuels strategies based on the Biomass Utilization Superstructure (BUS) framework. This web application allows researchers with limited knowledge of optimization to assess different technologies employed at different strategies and identify the major cost drivers. The user must only provide the necessary parameters and create an optimization run after identifying the question to be addressed and the assessment metric. The web application generates visual representations of the results once the optimal solution is obtained. Finally, we demonstrate the applicability of the web application through an example.

09 BIOMASS FUELS↗

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

97 MATHEMATICS AND COMPUTING↗

Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications

With building electric demand becoming increasingly dynamic, and a growing percentage of intermittent renewable power generation from solar photovoltaics and wind turbines, the power grid is facing increasing challenge to manage the real time balance between the supply and demand. With advancements in smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, demand side management of residential buildings can help the grid to improve stability by optimizing flexible loads. This paper reviews recent studies on residential building demand side management, with a focus on characterization and quantification of energy flexibility covering various types of flexible loads, metrics, methods, and applications. The reviewed studies showed four levels of applications: building level (45%), district or community level (29%), system level (19%), and building sector level (7%). Shifting loads is the dominant flexibility type in 60% of applications, followed by shedding (19%), generation (16%), and modulating (6%). Depending on the technology and application scope, flexible operations have a wide range of performance, with peak power reductions of 1%~65%, energy savings up to 60%, operational cost reduction of 1%~48%, and greenhouse gas emission reductions of up to29%. More than half (51%) of the studies employed control strategies to achieve flexibility; among those 72% used optimal controls, while 28% used rule-based controls. About 58% of the studies used mathematical formulation to quantify energy flexibility. Most studies were based on simulation, while less than 15% of the studies had measurements from experiments or field tests. The review reveals research opportunities to address significant gaps in the existing literature: (1) establishing a common definition and performance metrics for energy flexibility of buildings that are technology and application agnostic, (2) developing an ontology to standardize representation of flexibility resources for interoperability, (3) integrating occupant impacts into the quantification and optimization of energy flexibility, and (4) developing requirements and credits of energy flexibility in building energy codes and standards. Findings from the review can inform future research and development of energy flexible buildings which are essential to a reliable and resilient power grid.

Li, H↗

Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives

Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit about one-third of greenhouse gases. In the last few years, machine learning has achieved a notable momentum that, if properly harnessed, may unleash its potential for advanced analytics and control of smart buildings, enabling the technique to scale up for supporting the decarbonization of the building sector. In this perspective, transfer learning aims to improve the performance of a target learner exploiting knowledge in related environments. The present work provides a comprehensive overview of transfer learning applications in smart buildings, classifying and analyzing 77 papers according to their applications, algorithms, and adopted metrics. The study identified four main application areas of transfer learning: (1) building load prediction, (2) occupancy detection and activity recognition, (3) building dynamics modeling, and (4) energy systems control. Furthermore, the review highlighted the role of deep learning in transfer learning applications that has been used in more than half of the analyzed studies. The paper also discusses how to integrate transfer learning in a smart building's ecosystem, identifying, for each application area, the research gaps and guidelines for future research directions.

Pinto, G↗

Assessing the role of mini-applications in predicting key performance characteristics of scientific and engineering applications

Computational science and engineering application programs are typically large, complex, and dynamic, and are often constrained by distribution limitations. As a means of making tractable rapid explorations of scientific and engineering application programs in the context of new, emerging, and future computing architectures, a suite of miniapps has been created to serve as proxies for full scale applications. Each miniapp is designed to represent a key performance characteristic that does or is expected to significantly impact the runtime performance of an application program. In this paper we introduce a methodology for assessing the ability of these miniapps to effectively represent these performance issues. We applied this methodology to four miniapps, examining the linkage between them and an application they are intended to represent. Herein we evaluate the fidelity of that linkage. This work represents the initial steps required to begin to answer the question, ''Under what conditions does a miniapp represent a key performance characteristic in a full app?''

97 MATHEMATICS AND COMPUTING↗

Measurement and applications: Exploring the challenges and opportunities of hierarchical federated learning in sensor applications

Sensor applications have become ubiquitous in modern society as the digital age continues to advance. AI-based techniques (e.g., machine learning) are effective at extracting actionable information from large amounts of data. An example would be an automated water irrigation system that uses AI-based techniques on soil quality data to decide how to best distribute water. However, these AI-based techniques are costly in terms of hardware resources, and Internet-of-Things (IoT) sensors are resource-constrained with respect to processing power, energy, and storage capacity. These limitations can compromise the security, performance, and reliability of sensor-driven applications. To address these concerns, cloud computing services can be used by sensor applications for data storage and processing. Unfortunately, cloud-based sensor applications that require real-time processing, such as medical applications (e.g., fall detection and stroke prediction), are vulnerable to issues such as network latency due to the sparse and unreliable networks between the sensor nodes and the cloud server [1]. As users approach the edge of the communications network, latency issues become more severe and frequent. A promising alternative is edge computing, which provides cloud-like capabilities at the edge of the network by pushing storage and processing capabilities from centralized nodes to edge devices that are closer to where the data are gathered, resulting in reduced network delays [2], [3].

Po-Leen Ooi, Melanie↗

Application Potential of a Dew-Point Cooling Tower in Selected Energy Intensive Applications in Temperate Climate

In the article, the application potential of the dew-point cooling tower (DPCT) in selected energy-intensive applications in temperate climates was analyzed and discussed. The applications selected for analysis are power generation with natural gas turbines and chilled water air conditioning systems. The study is based on a mathematical model derived from a modified ε-NTU model. The model was validated against experimental results and showed satisfactory agreement with the experimental data. DPCT was compared with a typical cooling tower limited by the wet-bulb temperature (wet-bulb cooling tower, WBCT). The simulation results showed that DPCT is able to provide significant energy savings in energy-intensive applications; therefore, its application potential in temperate climates can be considered justified. In the case of gas turbines, DPCT was able to generate 2 to 10 percentage points more capacity than operating on outdoor air and 1.8 to 5 percentage points more than operating with WBCT. In the case of air conditioning systems, the system equipped with DPCT achieved EERs (energy efficiency ratios) higher by 1 to 7.2 compared to dry cooling and by 0.3 to 5.1 compared to systems equipped with WBCT. The annual energy savings obtained by the system with DPCT were 14.7 MWh compared to WBCT and 30 MWh compared to dry cooling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

With the increasing digitalization of processes throughout the lifecycle of buildings, data exchanged between stakeholders and between building systems has grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent, hindering the development of applications that can be reused across buildings and limiting the scalability of innovative solutions. Semantics refers to the description of the meaning of the data in a way that can be consistently understood by applications. Recently, several competing initiatives have been developing metadata schemas and ontologies to express this semantic information for different applications in the building domain. This paper systematically reviews these schemas and conducts an analysis of five of them to evaluate their applicability to three high-value use cases for building operations: energy audits, automated fault detection and diagnostics and optimal control. The survey finds 40 schemas published in the last 10 years but but their actual use in industry is difficult to estimate. Among the five selected ontologies, several gaps are highlighted in relation to the three use cases. Recommendations for the future include better harmonization of these initiatives, more centralized repositories and search engines for these schemas as well as better industry engagement to facilitate their adoption.

Smart Building, Sematic, Metadata, Ontology, Data ↗

NASA Application Team Program: Application of aerospace technology in biology and medicine

The results of the medically related activities of the NASA Application Team Program in technology application for the reporting period September 1, 1972, to August 31, 1973 are reported. The accomplishments of the application team during the reporting period are as follows: The team has identified 39 new problems for investigation, has accomplished 7 technology applications, 4 potential technology applications, 2 impacts, has closed 38 old problems, and has a total of 59 problems under active investigation.

Source record↗

Grid Application and Controls Development for Medium-Voltage SiC-Based Grid Interconnects

This paper studies, the grid-interconnection requirements of directly connected medium-voltage (MV) Silicon Carbide-based (SiC-based) converters and details the necessary control implementations. These power electronic converters follow the interconnection standard IEEE 1547-2018, but can also have additional controls supported by the microgrid standards in IEEE 2030.7, which is demonstrated in this work. Additionally, this paper defines the grid applications realized by these directly connected medium-voltage power electronic converters at the distribution scale and demonstrates results. The controls for the studied grid applications are then developed and implemented on the controller. The paper also includes details of the control algorithm development and validations of the control algorithm through hardware-in-the-loop results.

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