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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1978

Technology advances and market forces: Their impact on high performance architectures

Reasonable projections into future supercomputer architectures and technology require an analysis of the computer industry market environment, the current capabilities and trends within the component industry, and the research activities on computer architecture in the industrial and academic communities. Management, programmer, architect, and user must cooperate to increase the efficiency of supercomputer development efforts. Care must be taken to match the funding, compiler, architecture and application with greater attention to testability, maintainability, reliability, and usability than supercomputer development programs of the past.

Best, D. R.↗
NASA NTRS1998

Incompressible Turbulent Wing-Body Junction Flow

The overall objective of this study is to contribute to the optimized design of fan bypass systems in advanced turbofan engines. Increasing the engine bypass ratios have provided a major boost in engine performance improvement over the last fifty years. An engine with high bypass ratio (11-16:1) such as the Advanced Ducted Propulsion (ADP) is being developed and is expected to provide an additional 25% improvement in overall efficiency over the early turbofans. Such significant improvements in overall efficiency would reduce the cost per seat mile, which is a major government and Industry challenge for the 21th century. The research is part of the Advanced Subsonic Technology (AST) program that involves a NASA, U.S. Industry and FAA partnership with the goal of a safe and highly productive global air transportation system. The immediate objective of the study is to perform numerical simulation of duct-strut interactions to elucidate the loss mechanisms associated with this configuration that is typical of advanced turbofan engines such as ADP. However, at present experimental data for a duct-strut configuration are not available. Thus, as a first step a wing-body junction flow would be studied and is the specific objective of the present study. At the outset it is to be recognized that while duct-strut interaction flow is similar to that of wing-body junction flows, there are some differences owing to the presence of a wall at both ends of the strut. Likewise, some differences are due to the sheared inflow (as opposed to a uniform inflow) velocity profile. It is however expected that some features of a wing-body junction flow would persist. Next, some of the salient aspects of the complex flow near a wing-body junction, as revealed by various studies reported in the literature will be reviewed. One of the principle characteristics of the juncture flow, is the presence of the mean flow components in a plane perpendicular to the direction of the oncoming free-stream flow. The lateral curvature of the wing/strat causes the oncoming turbulent layer to skew about am axis (x-axis) parallel to the plane (xz-plane) of the mean shear. This is the principle mechanism for the generation of secondary flow. Such skew-induced secondary flows are slow to be attenuated by Reynolds stresses. Additional contribution to the generation of secondary flow comes from anisotropies in Reynolds stresses. Upstream of the strut, the mean-vorticity is directed span wise (along the y-direction). The presence of secondary flow in the vicinity of the strut causes the vorticity to stretch around the obstacle in a horse-shoe shape, with each leg having a vorticity of the opposite sense. The blockage effect of the strut imposes a severe adverse pressure gradient on the oncoming turbulent shear layer, causing boundary layer separation ahead of the leading edge, resulting in a vortex that rolls up and flows downstream into the juncture region. The separation vortices trailing in the wake of the wing can alter the lift or drag characteristics of the surfaces downstream of the wing-body juncture. Likewise, on submarines, the wake flow behind the appendage can degrade the performance of the propeller located downstream. The complex nature of this flow is caused by the presence of all six components of Reynolds stresses. Devenport and Simpson report that in the vicinity of the horse-shoe vortex there is intense recirculation with turbulent stresses being much larger than those normally observed in turbulent flows. These features contribute to making this flow a challenge to predict numerically. Some of the past studies provide useful insights into this flow that would guide our numerical efforts. In measurements reported by Shabaka and Bradshaw, the eddy viscosity tensor is seen to be non-isotropic and has negative components in certain regions. In an effort to evaluate the closure assumptions of various turbulence models, Devenport and Simpson used their own extensive measurements in juncture flows around the nose of a wing-body junction. Measured values of mean-velocity and/or turbulence kinetic energy was used to predict the magnitude of the shear stress vector. Algebraic stress models performed the best followed by Cebeci-Smith eddy viscosity model. The flow is reported to be dominated by a pressure field produced by the wing and the velocity field generated by the horseshoe vortex that is wrapped around the junction between the wing and wall. Kubendran et al. conclude from an experimental study that the shape of leading edge of the wing as characterized by its slenderness ratio is a major factor in determining the flow fields in the juncture region. The more thinner the leading edge of the juncture, the weaker the horseshoe vortex is. Also, with a slender leading edge, the secondary flow in the juncture would be due mainly to the cross-stream gradients of Reynolds stresses rather than due to a lateral skewing of the shear layer.

Krishnamurthy, R.↗
NASA NTRS2003

A Rational Approach to Determine Minimum Strength Thresholds in Novel Structural Materials

Design of safe and survivable structures requires the availability of guaranteed minimum strength thresholds for structural materials to enable a meaningful comparison of strength requirement and available strength. This paper develops a procedure for determining such a threshold with a desired degree of confidence, for structural materials with none or minimal industrial experience. The problem arose in attempting to use a new, highly weight-efficient structural load tendon material to achieve a lightweight super-pressure balloon. The developed procedure applies to lineal (one dimensional) structural elements. One important aspect of the formulation is that it extrapolates to expected probability distributions for long length specimen samples from some hypothesized probability distribution that has been obtained from a shorter length specimen sample. The use of the developed procedure is illustrated using both real and simulated data.

Schur, Willi W.↗
NASA NTRS2004

Future Concepts for Realtime Data Interfaces for Control Centers

Existing methods of exchanging realtime data between the major control centers in the International Space Station program have resulted in a patchwork of local formats being imposed on each Mission Control Center. This puts the burden on a data customer to comply with the proprietary data formats of each data supplier. This has increased the cost and complexity for each participant, limited access to mission data and hampered the development of efficient and flexible operations concepts. Ideally, a universal format should be promoted in the industry to prevent the unnecessary burden of each center processing a different data format standard for every external interface with another center. With the broad acceptance of XML and other conventions used in other industries, it is now time for the Aerospace industry to fully engage and establish such a standard. This paper will briefly consider the components that would be required by such a standard (XML schema, data dictionaries, etc.) in order to accomplish the goal of a universal low-cost interface, and acquire broad industry acceptance. We will then examine current approaches being developed by standards bodies and other groups. The current state of CCSDS panel work will be reviewed, with a survey of the degree of industry acceptance. Other widely accepted commercial approaches will be considered, sometimes complimentary to the standards work, but sometimes not. The question is whether de facto industry standards are in concert with, or in conflict with the direction of the standards bodies. And given that state of affairs, the author will consider whether a new program establishing its Mission Control Center should implement a data interface based on those standards. The author proposes that broad industry support to unify the various efforts will enable collaboration between control centers and space programs to a wider degree than is currently available. This will reduce the cost for programs to provide realtime access to their data, hence reducing the cost of access to space, and benefiting the industry as a whole.

Kearney, Mike W., III↗
NASA NTRS1999

Lightweight Battery Charge Regulator Used to Track Solar Array Peak Power

A battery charge regulator based on the series-connected boost regulator (SCBR) technology has been developed for high-voltage spacecraft applications. The SCBR regulates the solar array power during insolation to prevent battery overcharge or undercharge conditions. It can also be used to provide regulated battery output voltage to spacecraft loads if necessary. This technology uses industry-standard dc-dc converters and a unique interconnection to provide size, weight, efficiency, fault tolerance, and modularity benefits over existing systems. The high-voltage SCBR shown in the photograph has demonstrated power densities of over 1000 watts per kilogram (W/kg). Using four 150-W dc-dc converter modules, it can process 2500 W of power at 120 Vdc with a minimum input voltage of 90 Vdc. Efficiency of the SCBR was 94 to 98 percent over the entire operational range. Internally, the unit is made of two separate SCBR s, each with its own analog control circuitry, to demonstrate the modularity of the technology. The analog controllers regulate the output current and incorporate the output voltage limit with active current sharing between the two units. They also include voltage and current telemetry, on/off control, and baseplate temperature sensors. For peak power tracking, the SCBR was connected to a LabView-based data acquisition system for telemetry and control. A digital control algorithm for tracking the peak power point of a solar array was developed using the principle of matching the source impedance with the load impedance for maximum energy transfer. The algorithm was successfully demonstrated in a simulated spacecraft electrical system at the Boeing PhantomWorks High Voltage Test Facility in Seattle, Washington. The system consists of a 42-string, high-voltage solar array simulator, a 77-cell, 80-ampere-hour (A-hr) nickel-hydrogen battery, and a constant power-load module. The SCBR and the LabView control algorithm successfully tracked the solar array peak power point through various load transients, including sunlight discharge transients when the total load exceeded the maximum solar array output power.

Soeder, James F.↗
NASA NTRS2006

Development of a New Generation of High-Temperature Thermoelectric Unicouples for Space Applications

RTG's have enabled surface and deep space missions since 1961: a) 26 flight missions without any RTG failures; and b) Mission durations in excess of 25 years. Future NASA missions require RTG s with high specific power and high efficiency, while retaining long life (> 14 years) and high reliability, (i.e. 6-8 W/kg, 10-15% efficiency). JPL in partnership with NASA-GRC, NASA-MSFC, DOE, Universities and Industry is developing advanced thermoelectric materials and converters to meet future NASA needs.

Radioisotope Thermoelectric Generator↗
NASA NTRS2012

The Economics of NASA Mission Cost Reserves

Increases in NASA mission costs are well-noted but not well-understood, and there is little evidence that they are decreasing in frequency or amount over time. The need to control spending has led to analysis of the causes and magnitude of historical mission overruns, and many program control efforts are being implemented to attempt to prevent or mitigate the problem (NPR 7120). However, cost overruns have not abated, and while some direct causes of increased spending may be obvious (requirements creep, launch delays, directed changes, etc.), the underlying impetus to spend past the original budget may be more subtle. Gaining better insight into the causes of cost overruns will help NASA and its contracting organizations to avoid .them. This paper hypothesizes that one cause of NASA mission cost overruns is that the availability of reserves gives project team members an incentive to make decisions and behave in ways that increase costs. We theorize that the presence of reserves is a contributing factor to cost overruns because it causes organizations to use their funds less efficiently or to control spending less effectively. We draw a comparison to the insurance industry concept of moral hazard, the phenomenon that the presence of insurance causes insureds to have more frequent and higher insurance losses, and we attempt to apply actuarial techniques to quantifY the increase in the expected cost of a mission due to the availability of reserves. We create a theoretical model of reserve spending motivation by defining a variable ReserveSpending as a function of total reserves. This function has a positive slope; for every dollar of reserves available, there is a positive probability of spending it. Finally, the function should be concave down; the probability of spending each incremental dollar of reserves decreases progressively. We test the model against available NASA CADRe data by examining missions with reserve dollars initially available and testing whether they are more likely to spend those dollars, and whether larger levels of reserves lead to higher cost overruns. Finally, we address the question of how to prevent reserves from increasing mission spending without increasing cost risk to projects budgeted without any reserves. Is there a "sweet spot"? How can we derive the maximum benefit associated with risk reduction from reserves while minimizing the effects of reserve spending motivation?

Whitley, Sally↗
NASA NTRSDate not supplied

Stiffness and Fatigue Life Estimator for Polymer Composite Laminates Using Machine Learning

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.

multiscale analysis↗
NASA NTRS2023

Stiffness and Fatigue Life Estimator for Polymer Composite Laminates Using Machine Learning

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.

multiscale analysis↗
NASA NTRSDate not supplied

NASA Power: Global Solar Insolation, Meteorological Parameter Data, and Web Services to Support Sustainable Building Design and Operations

The buildings industry is currently striving to adopt green solutions to make infrastructure more energy-efficient in order to meet the 2050 net-zero climate goals. This planning requires reliable environmental datasets that are crucial in designing, building, and maintaining our world’s-built environment, as well as other energy-related processes and investments. This webinar for the National Institute of Building Sciences provides an overview of NASA’s Prediction Of Worldwide Energy Resources (POWER) Project that informs decision-making and development for sustainable building design and operations by enabling public open discovery, efficient access, and convenient distribution of NASA’s Earth Observations and global atmospheric model datasets. POWER’s datastore is comprised of solar radiation and surface meteorology parameters, spanning nearly 40 years of hourly data, that are easily accessible via several access methods and tools to support three focus areas: 1) renewable energy deployment and management, 2) sustainable infrastructure, and 3) agroclimatology applications. POWER and NASA Earth Science both plan future data parameters, updated tools, and improved observations that could directly support U.S. and international sustainable development goals, climate strategies, and building information modeling. To this end, solar data from several NASA projects and meteorological data from NASA assimilation models have already been reformatted and disseminated to the public via a user-friendly web GIS-enabled based data portal through the POWER Project. POWER data is analysis-ready and accessible through an Application Programming Interface (API), ArcGIS Image Services, and the project’s Data Access Viewer enhanced (DAVe), an interactive online tool. The POWER DAVe also features data consistent with ASHRAE Climate Design Conditions and has developed web image services showing Building Climate Zones and their variability. Through those tools, the data can be downloaded into multiple formats that support the infrastructure community, including CSV and Energy Plus Weather (EPW). POWER’s entire data product catalog is available through Amazon Web Services (AWS) Open Data Registry (ODR) via a free and publicly accessible Simple Storage Service (S3). This webinar provides a full overview of the NASA POWER Project's data and services developed in collaboration with the sustainable infrastructure community. Examples of how the renewable energy and building communities have utilized POWER data products to make decisions and a preview of future data product expansion, including climate projections, and web services will also be provided. Additionally, use case stories from our broad community of users will be presented.

Paul W. Stackhouse↗
DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Forced RF generation of CW magnetrons for superconducting accelerators

CW magnetrons, designed and optimized for industrial RF heaters, were suggested to power Superconducting RF cavities due to their higher efficiency and lower cost than traditional klystrons, IOT’s, or solid-state amplifiers. RF amplifiers driven by a master-oscillator serve as coherent RF sources. CW magnetrons are regenerative RF generators with a huge regenerative gain. Very large regenerative gain causes instability with intense noise when a magnetron operates with the anode voltage higher than the threshold of self-excitation. Traditionally for stabilization of magnetrons is used injection-locking by a quite small signal. In this case the CW magnetrons do not provide correlation of the magnetron startup with the injection-locking signal. Thus, the magnetron except the injection locked oscillations may generate large noise. This may increase emittance of the beam in SRF accelerators. Recently we have developed mode for forced RF generation of CW magnetrons when the magnetron startup is provided by the injected forcing signal and the regenerative noise is suppressed. The mode is most suitable for SRF accelerators. The mode is briefly described below.

43 PARTICLE ACCELERATORS↗
NASA NTRS2006

NASA Solar Array Demonstrates Commercial Potential

A state-of-the-art solar-panel array demonstration site at NASA's Dryden Flight Research Center provides a unique opportunity for studying the latest in high-efficiency solar photovoltaic cells. This five-kilowatt solar-array site (see Figure 1) is a technology-transfer and commercialization success for NASA. Among the solar cells at this site are cells of a type that was developed in Dryden Flight Research Center s Environmental Research Aircraft and Sensor Technology (ERAST) program for use in NASA s Helios solar-powered airplane. This cell type, now denoted as A-300, has since been transferred to SunPower Corporation of Sunnyvale, California, enabling mass production of the cells for the commercial market. High efficiency separates these advanced cells from typical previously commercially available solar cells: Whereas typical previously commercially available cells are 12 to 15 percent efficient at converting sunlight to electricity, these advanced cells exhibit efficiencies approaching 23 percent. The increase in efficiency is due largely to the routing of electrical connections behind the cells (see Figure 2). This approach to increasing efficiency originated as a solution to the problem of maximizing the degree of utilization of the limited space available atop the wing of the Helios airplane. In retrospect, the solar cells in use at this site could be used on Helios, but the best cells otherwise commercially available could not be so used, because of their lower efficiencies. Historically, solar cells have been fabricated by use of methods that are common in the semiconductor industry. One of these methods includes the use of photolithography to define the rear electrical-contact features - diffusions, contact openings, and fingers. SunPower uses these methods to produce the advanced cells. To reduce fabrication costs, SunPower continues to explore new methods to define the rear electrical-contact features. The equipment at the demonstration site includes two fixed-angle solar arrays and one single-axis Sun-tracking array. One of the fixed arrays contains typical less-efficient commercial solar cells and is being used as a baseline for comparison of the other fixed array, which contains the advanced cells. The Sun-tracking array tilts to follow the Sun, using an advanced, real-time tracking device rather than customary pre-programmed mechanisms. Part of the purpose served by the demonstration is to enable determination of any potential advantage of a tracking array over a fixed array. The arrays are monitored remotely on a computer that displays pertinent information regarding the functioning of the arrays.

Creech, Gray↗
DOE OSTI2025

Integration of hydrophobic gas diffusion layers for zero-gap electrolyzers to enable highly energy-efficient CO 2 electrolysis to C 2 products

Electrochemical CO 2 reduction (eCO2R) is an attractive route for mitigating global CO 2 emissions while producing value-added chemicals. Ethylene is one product of eCO2R and is an essential industrial precursor with a global market of $230 billion. The large-scale implementation of C 2 H 4 -selective CO 2 electrolyzers remains challenging because of low energy efficiencies. In this work, we develop the design principles necessary for incorporating an expanded polytetrafluoroethylene (ePTFE) electrode into a zero-gap electrolyzer while simultaneously developing an integrated electrical front contact that reduces the ohmic resistances inherent to electrically insulating gas diffusion layers. By co-designing the catalyst layer, gas diffusion medium, and operating conditions for a zero-gap ePTFE gas diffusion electrode (GDE), we achieved a full-cell voltage of 2.5 V at 200 mA cm −2 at 25 cm 2 geometric area cell with Faradaic efficiencies of 48% for ethylene and 40% for ethanol. This work highlights strategies for developing a scalable, stable, and highly energy-efficient eCO2R for C 2 products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

6 th International Conference on Plant Synthetic Biology, Bioengineering and Biotechnology (Workshop Report)

The objective of the project is to hold a Conference to bring together scientists and engineers from universities, industry and government working in all aspects of plant synthetic biology, plant bioengineering and plant biotechnology. To meet this objective, AIChE will host the 6th International Conference on Plant Synthetic Biology, Bioengineering and Biotechnology on December 9-11, 2022 in Fort Lauderdale, Florida. The conference will feature five technical sessions: (1) Genome and Epigenome Editing, (2) Specialized Metabolism, (3) Engineering Plant Resilience, (4) Engineering more efficient plants, and (5) New tools and Technologies. The conference will allow leading scientists and engineers from universities, industry and government to discuss new tools and technologies being developed as well as their applications, and gaps in the field. The conference will allow students to learn about these new technologies, engage in a discussion with professionals in their field of interest, and showcase their work. The scope, theme, and aims of the Conference on Plant Synthetic Biology, Bioengineering, and Biotechnology fall squarely within the mission of DOE which includes securing US leadership in energy technology and to maintaining a vibrant US effort in science and engineering as a cornerstone for our economic prosperity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Robust Online Sequential RVFLNs for Data Modeling of Dynamic Time-Varying Systems with Application of an Ironmaking Blast Furnace

In a world where the increasing complexity of modern industrial processes brings difficulties for accurate mathematical modeling, taking advantage of data has become an efficient solution to complex dynamic process modeling issue. In this paper, we develop a novel robust online sequential version of random vector functional-link networks (RVFLNs) for data-driven modeling of dynamic time-varying system and applied it in a blast furnace (BF) ironmaking process. First, to overcome the time-varying dynamics of process and to enable the RVFLNs to learn online with avoiding data saturation, an improved online sequential version of RVFLNs (OS-RFVLNs) is first presented by online sequential learning with forgetting factor. This improved OS-RVFLNs algorithm is not only suitable for the real-time and large data transfer situation, but also can adjust the sensitivity of the algorithm to different samples with the help of the introduced forgetting factor. Second, since the output weights of the improved OS-RVFLNs as well as other RVFLNs algorithms are obtained by the least squares approach, a robustness problem may occur when the training dataset is contaminated with various outliers. To solve this problem, a Cauchy distribution weighted M-estimator is introduced to improve the robustness of the improved OS- RVFLNs. For this proposed robust OS-RVFLNs (R-OS- RVFLNs), since the weights of different outlier data are properly determined by the Cauchy distribution function, their corresponding contribution on modeling can be properly distinguished. Thus robust and better modeling results can be achieved. Experiments using actual industrial data of BF ironmaking process and comparative studies have demonstrated that the proposed method produces a better estimation accuracy and stronger robustness than other methods.

Blast furnace (BF), Modelling, Dynamic systems↗
DOE OSTI2022

Demand Response in Industrial Facilities: Peak Electric Demand

The US Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) is a voluntary energy efficiency leadership initiative for US manufacturers and water/wastewater entities. The program encourages organizations to commit to reducing the energy intensity of their US operations over a 10-year period, typically by 25%. Companies joining Better Plants are recognized by DOE for their leadership in implementing energy efficiency practices and for reducing their energy intensity. Better Plants Partners are assigned to a Technical Account Manager, who can help companies establish energy intensity baselines, develop energy management plans, and identify key resources and incentives from DOE, other federal agencies, states, utilities, and other organizations that can enable them to reach their goals. Better Plants Partners are expected to report their progress to DOE once a year. This involves establishing an energy intensity baseline upon joining the program and then tracking their progress over time. Demand Response in Industrial Facilities: Peak Electrical Demand is intended to help companies understand peak demand response programs offering by their local utility. Manufacturing industries can learn about time-varying rates and smart technologies they can use to help them reduce their energy bills. This guidance document is applicable to companies participating at either the program or challenge level. Although this guide is intended primarily to assist companies participating in Better Plants, the methodologies and guidance within the document are applicable to any organization interested in understanding peak demand response programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗