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At least 1,567 records · Page 87

Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation

This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define "explicit" input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAE 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Using Information Automation and Human Technology Integration to Implement Integrated Operations for Nuclear

The purpose of the research effort described in this report is to develop and demonstrate an approach to the design and implementation of advanced, automated systems intended to increase operational efficiencies at nuclear power plants. In particular, we describe methods for considering human-technology integration (HTI) issues throughout the various phases of system design, test, and implementation and how these considerations help promote effective design. This research project will develop planning tools and comprehensive guidance on how HTI principles and methods, in combination with information automation technologies, can enable effective data integration and coordination for full nuclear plant modernization. Specifically, this research project will develop an approach to automate the mapping of data from plant systems and processes to application needs, thereby significantly reducing the amount of human workload currently required for the execution of these tasks. In addition to developing an automated solution as a replacement for these tasks, this research will also analyze digitalization’s effectiveness in reducing operational costs of compliance related activities. Compliance activities are estimated to account for as much as 50% of operations and maintenance (i.e., non-fuel and non-capital) costs of plant operation.

97 MATHEMATICS AND COMPUTING↗

Model Based Validation of Intelligent Powertrain Strategies for Connected and Automated Vehicles

Systems incorporating Vehicle to Everything (V2X) and conventional cellular based communication in vehicles can significantly help improve energy consumption via a combination of intelligent powertrain control strategies, smarter routing algorithms and driving in such a way as to minimize fuel economy and the emission of carbon dioxide, known as "eco-driving." In projects led by the Southwest Research Institute (SwRI), large-scale traffic simulations are created to model real-world scenarios with dynamic behavior that is reactive to imposed changes. Coupled with high fidelity powertrain models, the closed loop framework enables research and development of such Connected and Automated Vehicle (CAV) enabled technologies at scale. This paper will discuss a traffic system simulation environment that was built based on the High Street urban corridor in Columbus, Ohio. Eco-driving strategies were tested at scale on a variety of powertrain platforms – internal combustion engines, hybrid electric and fully electric vehicles. Furthermore, the paper will focus on hybrid electric powertrain modeling along with details on how the powertrain model was leveraged to develop a sophisticated clustering scheme to help down-select speed traces from large scale simulation studies for validation on vehicle dynamometer. Nominal energy consumption improvement around 12% was observed with good match between simulation studies and vehicle testing.

33 ADVANCED PROPULSION SYSTEMS↗

Space missions for automation and robotics technologies (SMART) program

The motivations, features and expected benefits and applications of the NASA SMART program are summarized. SMART is intended to push the state of the art in automation and robotics, a goal that Public Law 98-371 mandated be an inherent part of the Space Station program. The effort would first require tests of sensors, manipulators, computers and other subsystems as seeds for the evolution of flight-qualified subsystems. Consideration is currently being given to robotics systems as add-ons to the RMS, MMU and OMV and a self-contained automation and robotics module which would be tended by astronaut visits. Probable experimentation and development paths that would be pursued with the equipment are discussed, along with the management structure and procedures for the program. The first hardware flight is projected for 1989.

Ciffone, D. L.↗

Novel Algae Technology to Utilize CO 2 for Value Added Products

The Helios-NRG technology for converting coal-based flue CO 2 into valuable products has been successfully validated through a series of rigorous test programs. The key component, the MSC (Multi Stage Continuous System), played a pivotal role in this process. The MSC's various stages were seamlessly integrated and controlled by a second-generation automated system, surpassing project goals in terms of both algal productivity and capture efficiency. Notably, the MSC's operational duration improved while maintaining healthy cultures. The integrated system was rigorously tested under real outdoor conditions with varying sunlight levels and template flue gas. The final MSC test, conducted at the NCCC, successfully met project objectives.

01 COAL, LIGNITE, AND PEAT↗

About Small Streams and Shiny Rocks: Macromolecular Crystal Growth in Microfluidics

We are developing a novel technique with which we have grown diffraction quality protein crystals in very small volumes, utilizing chip-based, microfluidic ("LabChip") technology. With this technology volumes smaller than achievable with any laboratory pipette can be dispensed with high accuracy. We have performed a feasibility study in which we crystallized several proteins with the aid of a LabChip device. The protein crystals are of excellent quality as shown by X-ray diffraction. The advantages of this new technology include improved accuracy of dispensing for small volumes, complete mixing of solution constituents without bubble formation, highly repeatable recipe and growth condition replication, and easy automation of the method. We have designed a first LabChip device specifically for protein crystallization in batch mode and can reliably dispense and mix from a range of solution constituents. We are currently testing this design. Upon completion additional crystallization techniques, such as vapor diffusion and liquid-liquid diffusion will be accommodated. Macromolecular crystallization using microfluidic technology is envisioned as a fully automated system, which will use the 'tele-science' concept of remote operation and will be developed into a research facility aboard the International Space Station.

vanderWoerd, Mark↗

Results of prototype software development for automation of shuttle proximity operations

The effort involves demonstration of expert system technology application to Shuttle rendezvous operations in a high-fidelity, real-time simulation environment. The JSC Systems Engineering Simulator (SES) served as the test bed for the demonstration. Rendezvous applications were focused on crew procedures and monitoring of sensor health and trajectory status. Proximity operations applications were focused on monitoring, crew advisory, and control of the approach trajectory. Guidance, Navigation, and Control areas of emphasis included the approach, transition and stationkeeping guidance, and laser docking sensor navigation. Operator interface displays for monitor and control functions were developed. A rule-based expert system was developed to manage the relative navigation system/sensors for nominal operations and simple failure contingencies. Testing resulted in the following findings; (1) the developed guidance is applicable for operations with LVLH stabilized targets; (2) closing rates less than 0.05 feet per second are difficult to maintain due to the Shuttle translational/rotational cross-coupling; (3) automated operations result in reduced propellant consumption and plume impingement effects on the target as compared to manual operations; and (4) braking gates are beneficial for trajectory management. A versatile guidance design was demonstrated. An accurate proximity operations sensor/navigation system to provide relative attitude information within 30 feet is required and redesign of the existing Shuttle digital autopilot should be considered to reduce the cross-coupling effects. This activity has demonstrated the feasibility of automated Shuttle proximity operations with the Space Station Freedom. Indications are that berthing operations as well as docking can be supported.

Hiers, Hal↗

Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) in Support of Plant-Growth Systems

As the National Aeronautics and Space Association (NASA) begins to pursue long-duration space flights, they will need to be able to provide astronauts with a nutritious and reliable food source. To meet the administration’s goal of traveling to the Moon and Mars, astronauts will need to begin to grow their own food in space. To protect their food source, extensive monitoring will occur to test for the effects of a space flight environment (e.g., radiation) as well as for early pathogen and disease detection. Genomic sequencing allows for both concerns to be tested on a regular basis. However, NASA’s current sequencer is unable to process plant tissues. Therefore, a novel method for plant DNA extraction using microneedle (MN) patches that will be able to feed into NASA’s existing system, but also require minimal human input is proposed. To support this, the design was broken down into four components (1) MN patch fabrication (2) MN patch extraction, (3) automated sampling motion control, and (4) a processing module. The MN patch is fabricated using a custom mold with conically shaped needles. The mold is filled with Polyvinyl alcohol (PVA) solution and placed in a vacuum desiccator. The mold is left in the vacuum overnight until the patch is dry and ready for use. The protocol was tested with varying pressures, drying times, volume amounts, and preparation methods to determine if highquality needles can be produced. A MN is a method of DNA extraction where the patch is applied to a leaf, the needles penetrate the leaf, breaking the rigid plant cell wall to isolate the DNA. A protocol for this method of extraction was tested to ensure the patch could produce the needed yield and purity. The tests varied by the number of patches, number of applications, and plant type. To automate the MN extraction method, motion control will utilize two separate axis tables which move in the x and y directions. The y-axis table will have an end effector that fits a MN patch and will have the ability to apply the patch to the leaf sample. This end effector will also act as a lid for a downstream processing module. The other axis will position the leaf sample and processing container so that the patch can be applied accurately. The Joint Comprehensive Sequencing System (JCSS) module integrates all the components together. The output of this module feeds into the NASA Charged Information-Storage Polymer Preparation System (CHIPPS) for genomic sequencing. The extraction module operates using a series of syringes and tubing to pump the varying reagents needed for the extraction protocol. The results of the study proved that MN patches are a viable method of DNA extraction. While fabrication of high-quality needles was unsuccessful, the protocol was able to be further developed using centrifugation. The integrated design between the motion control and the JCSS enabled the potential for automation with a complete conceptual design and prototype. Future research and development for this study would include (1) further testing for fabrication (2) expanding the range of plant species compatible with the MN patch, and (3) building a working prototype for the integrated system.

Peter Ling↗

Sample problems for Section III, Division 5 design by inelastic analysis of Grade 91 components

This report works through two sample design analyses of representative Grade 91 components using the ASME Boiler & Pressure Vessel Code Section III, Division 5, Appendix HBB-T rules for the strain and deformation and creep-fatigue design criteria using a design by inelastic analysis approach. The component geometries and loadings were selected to span a wide variety of potential applications. The sample components are an endplate geometry, which is fairly representative of typical pressure vessel construction, and a core block, representing a critical component in a heat pipe microreactor, which has a complicated geometry and complex thermal stress history. These sample problems serve several functions. First, they are complete worked examples of how to apply the current design by inelastic analysis rules. Second, they serve as test cases to evaluate the current rules and provide feedback on how they could be optimized to deal with complicated component geometries or to be better automated in modern finite element analysis software. Finally, the analysis here uses an inelastic constitutive model for Grade 91 developed by Argonne National Laboratory and proposed for inclusion in the ASME Boiler & Pressure Vessel Code Section III, Division 5 rules as a reference constitutive model. Using this constitutive model in the sample problem analyses tests the model in the context of the ASME Code rules. The final conclusions of this report are that the material model and the current Code rules are satisfactory, but that the Code rules could be optimized to simplify automation and reduce over conservatism. Future work should address the specific optimization topics discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Indoor Occupant Counting by RF Backscattering

Building HVAC (heating, ventilation and air conditioning) consumes approximately 13% of all energy consumption in USA. Motion detectors, cameras and user programmable thermostats have been shown to be ineffective for HVAC controls to save energy, mostly due to the user concerns of comfort, reliability and privacy. A new HVAC control system based on real-time occupant counting that is fully automated, highly accurate, economically sensible and preserving privacy and aesthetics can thus bring forth a disruptive impact to this large energy sector. Our indoor occupant monitoring technology is based on the radio-frequency identification system (RFID), deployed in the room, not on the occupants. One reader with four antennas can be deployed on the ceiling or behind the ceiling panels for every thousand square feet in home, office and assisted living, with or without room partitions. The sticker-like passive tag, 10 cents each and maintenance-free, are profusely hidden on the wall or inside the furniture at arbitrary position, preserving privacy and aesthetics. The large number of tags can realize diverse observation points to accommodate arbitrary room layouts, which is impractical by other active units of camera, infrared, radar or lidar. With 20 tags, the system can reliably detect the number of occupants. For 100 tags, occupant posture and location can be known. The technology has been verified in the research labs and test buildings with very high accuracy. When the real-time occupant number can be accurately known without assuming devices on occupants or occupant motion, the building HVAC system can be automated to achieve building energy saving without sacrificing occupant comfort. According to our limited testing in a few types of building models and the simplified cost calculation, the RFID system has low overall cost in production, deployment, operation and maintenance. The signal processing algorithm based on machine learning requires very small number of training cases as most learning is transferrable for various layouts, and very low computational needs during operation, according to our testing in four different room sizes and layouts. In our preliminary estimate from HVAC saving alone, the RFID system can potentially pay for itself within 1.5 years, in addition to the other enhancement in building automation systems (BAS). Our commercialization strategy and business pitch deck focus on venturing this Cornell occupant monitoring technology into BAS and energy management markets. We have identified three broad BAS market segments of senior living, residential buildings, and office buildings. We have put together the minimum viable product characteristics for these identified segments, including analyses on total cost and competing technologies, as well as the fit and technical gaps for these market segments. We intend to bring the technology to market by licensing or partnering with existing BAS vendors. A list of potential collaborators and licensing partner candidates was assembled for different aspects of integrating our technology into a potential product that can be used with BAS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Containerization in ATLAS Software Development and Data Production

The ATLAS experiment's software production and distribution on the grid benefits from a semi-automated infrastructure that provides up-to-date information about software usability and availability through the CVMFS dis-tribution service for all relevant systems. The software development process uses a Continuous Integration pipeline involving testing, validation, packag-ing and installation steps. For opportunistic sites that can not access CVMFS, containerized releases are needed. These standalone containers are currently created manually to support Monte-Carlo data production at such sites. In this paper we will describe an automated procedure for the containerization of AT-LAS software releases in the existing software development infrastructure, its motivation, integration and testing in the distributed computing system.

97 MATHEMATICS AND COMPUTING↗

Development of an Automated J-R Curve Analysis Software Based on the ASTM E1820-18 Normalization Method

The J-integral versus crack-growth resistance curve (J-R curve) is a useful tool for evaluating material fracture toughness in the ductile region. A widely accepted practice for conducting J-R curve testing is ASTM standard E1820, which introduces the normalization method. This method does not require compliance measurements during testing, significantly simplifying J-R curve testing compared with the conventional elastic unloading compliance (EUC) method. Despite the advantage in testing, analysis procedures for the normalization method are very complicated. Also, there is no open source software currently available to perform such analysis.The authors developed an open source automated J-R curve-analysis software based on the normalization method in ASTM E1820-18. Source codes were written in MATLAB and the compiled software, in the form of a stand-alone executable, has a user-friendly graphic interface and is readily compatible with modern Windows operating systems. Both source codes and the compiled executable file are available for download at https://code.ornl.gov/xc8/ANJR.git. Comparisons between resulting J-R curves from the software and manual analysis procedures show essentially identical results, indicating the suitability of applying the automated software for J-R curve analysis.

36 MATERIALS SCIENCE↗

A self-supervised workflow for particle picking in cryo-EM

High-resolution single-particle cryo-EM data analysis relies on accurate particle picking. To facilitate the particle picking process, a self-supervised workflow has been developed. This includes an iterative strategy, which uses a 2D class average to improve training particles, and a progressively improved convolutional neural network for particle picking. To automate the selection of particles, a threshold is defined (%/Res) using the ratio of percentage class distribution and resolution as a cutoff. This workflow has been tested using six publicly available data sets with different particle sizes and shapes, and can automatically pick particles with minimal user input. The picked particles support high-resolution reconstructions at 3.0 Å or better. This workflow is a step towards automated single-particle cryo-EM data analysis at the stage of particle picking. It may be used in conjunction with commonly used single-particle analysis packages such as Relion , cryoSPARC , cisTEM , SPHIRE and EMAN2 .

2D class averages↗

PHEV Real World Driving Cycle Energy and Fuel and Consumption Reduction Potential for Connected and Automated Vehicles

This paper presents real-world driving energy and fuel consumption results for the second-generation Chevrolet Volt plug-in hybrid electric vehicle (PHEV). A drive cycle, local to Michigan Technological University, was designed to mimic urban and highway driving test cycles in terms of distance, transients and average velocity, but with significant elevation changes to establish an energy intensive real-world driving cycle for assessing potential energy savings for connected and automated vehicle (CAV) control. The investigation began by establishing baseline and repeatability of energy consumption at various battery states of charge. It was determined that drive cycle energy consumption under a randomized set of boundary conditions varied within 3.6% of mean energy consumption regardless of initial battery state of charge. After completing 30 baseline drive cycles, a design for six sigma (DFSS) L18 array was designed to look at sensitivity of a range of parameters to energy consumption as related to connected and automated vehicles to target highest return on engineering development effort. The parameters explored in the DFSS array that showed the most sensitivity, in order of importance, were battery state of charge, vehicle mass, propulsion system thermal conditioning, HVAC setting and driver behavior. Each of these areas are explored for energy savings and discussed briefly in the context of CAV control opportunity for energy savings potential.

33 ADVANCED PROPULSION SYSTEMS↗

High Density Vertiplex - Scalable Autonomous Operations - Flight Test Report

This Technical Memorandum describes the approach taken within the High Density Vertiplex Project to perform rapid prototyping and assessment of the UAM Ecosystem including representative: Onboard Autonomous Systems, Ground Control and Fleet Management Systems, Airspace Management Systems, and Vertiport Automation Systems (VAS). Small Uncrewed Aerial Systems (sUAS) were employed as effective low risk and inexpensive surrogates for larger proposed UAM aircraft to accelerate the prototyping effort, ensure safety, greatly mitigate costs, and accelerate progress. Flight testing performed included multivehicle operations where usability Human Factors (HF) data was collected on the operators.

Jacob Schaefer↗

Development of a data-driven neural network model for electron thermal transport in NSTX

A data-driven electron thermal transport neural network (ETT-NN) model, trained on TRANSP interpretative analysis results of National Spherical Torus Experiment (NSTX), was developed to enable faster and more accurate ETT computation for spherical tokamaks (STs). The model incorporates both convolutional NNs and recurrent NNs, allowing it to simultaneously account for the spatial and temporal non-localities and multi-scale features of turbulent transport, which have been considered only in a limited manner in conventional models. The model was validated through interpretative analysis and predictive simulations using Tokamak Reactor Integrated Automated Suite for Simulation and Computation, demonstrating relatively high accuracy. Additionally, parameter scans were performed on test discharges known to exhibit specific turbulent modes, such as microtearing mode, trapped electron mode, kinetic ballooning mode, and electron temperature gradient mode. The scanning results revealed that the ETT-NN model exhibits the same trends as those observed in conventional gyrokinetic simulations or theories, while also capturing the global nature of turbulent transport, indicating that the data-driven model accurately reflects the underlying physical characteristics. Furthermore, due to the dimensionless nature of the model, we can feasibly expand its applicability by incorporating data from other devices and uncovering the characteristics of ETT in STs in the future.

NSTX↗

Scaling the PuNDIT project for wide area deployments

In today’s world of distributed scientific collaborations, there are many challenges to providing reliable inter-domain network infrastructure. Network operators use a combination of active monitoring and trouble tickets to detect problems, but these are often ineffective at identifying issues that impact wide-area network users. Additionally, these approaches do not scale to wide area inter-domain networks due to unavailability of data from all the domains along typical network paths. The Pythia Network Diagnostic InfrasTructure (PuNDIT) project aims to create a scalable infrastructure for automating the detection and localization of problems across these networks. The project goal is to gather and analyze metrics from existing perfSONAR monitoring infrastructures to identify the signatures of possible problems, locate affected network links, and report them to the user in an intuitive fashion. Simply put, PuNDIT seeks to convert complex network metrics into easily understood diagnoses in an automated manner. We present our progress in creating the PuNDIT system and our status in developing, testing and deploying PuNDIT. We report on the project progress to-date, describe the current implementation architecture and demonstrate some of the various user interfaces it will support. We close by discussing the remaining challenges and next steps and where we see the project going in the future.

97 MATHEMATICS AND COMPUTING↗