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Report describes operation, installation, and performance of solar-energy system which provides alternative to natural gas pool heating. System is comprised of 2,500 square feet of liquid flat-plate collectors connected to 3,600 galloon; gallongalloon storage tank, with microcomputer-based controls. Extension of building incorporates vertical-wall, passive collection system which provides quarter of heated fresh air for office.
The Goddard Space Flight Center Spacecraft Magnetic Test Facility (SMTF) was constructed in the 1960's for the purpose of simulating geomagnetic and interplanetary magnetic field environments. The facility includes a three axis Braunbek coil system consisting of 12 loops, 4 loops on each of the three orthogonal axes; a remote Earth field sensing magnetometer and servo controller; and a remote power control and instrumentation building. The inner coils of the Braunbek system are 42-foot in diameter with a 10-foot by 10-foot opening through the outer coils to accommodate spacecraft access into the test volume. The physical size and precision of the facility are matched by only two other such facilities in the world. The facility was used extensively from the late 1960's until the early 1990's when the requirement for spacecraft level testing diminished. New NASA missions planned under the Living with a Star, Solar Terrestrial Probes, Explorer, and New Millennium Programs include precision, high-resolution magnetometers to obtain magnetic field data that is critical to fulfilling their scientific mission. It is highly likely that future Lunar and Martian exploration missions will also use precision magnetometers to conduct geophysical magnetic surveys. To ensure the success of these missions, ground-testing using a magnetic test facility such as the GSFC SMTF will be required. This paper describes the history of the facility, the future mission requirements that have renewed the need for spacecraft level magnetic testing, and the plans for restoring the facility to be capable of performing to its original design specifications.
The Goddard Space Flight Center Spacecraft Magnetic Test Facility (SMTF) was constructed in the 1960's for the purpose of simulating geomagnetic and interplanetary magnetic field environments. The facility includes a three axis Braunbek coil system consisting of 12 loops, 4 loops on each of the three orthogonal axes; a remote Earth field sensing magnetometer and servo controller; and a remote power control and instrumentation building. The inner coils of the Braunbek system are 42-foot in diameter with a 10-foot by 10-foot opening through the outer coils to accommodate spacecraft access into the test volume. The physical size and precision of the facility are matched by only two other such facilities in the world. The facility was used extensively from the late 1960's until the early 1990's when the requirement for spacecraft level testing diminished. New NASA missions planned under the Living with a Star, Solar Terrestrial Probes, Explorer, and New Millennium Programs include precision, high-resolution magnetometers to obtain magnetic field data that is critical to fulfilling their scientific mission. It is highly likely that future Lunar and Martian exploration missions will also use precision magnetometers to conduct geophysical magnetic surveys. To ensure the success of these missions, ground testing using a magnetic test facility such as the GSFC SMTF will be required. This paper describes the history of the facility, the future mission requirements that have renewed the need for spacecraft level magnetic testing, and the plans for restoring the facility to be capable of performing to its original design specifications.
The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.
The U.S. Nuclear Regulatory Commission (NRC) staff reviews the human factors engineering (HFE) aspects of nuclear power plants in accordance with the Standard Review Plan (NUREG-0800, Standard Review Plan for the Review of Safety Analysis Reports for Nuclear Power Plants: LWR Edition). The Human Factors Engineering Program Review Model (NUREG-0711, Revision 3, issued November 2012) contains detailed design review procedures. As part of the review process, the interfaces between plant personnel and the plant's systems and components are evaluated for conformance with HFE guidelines. This document, Human-System Interface Design Review Guidelines (NUREG-0700, Revision 3), provides the guidelines necessary to perform this evaluation. The review guidelines address the physical and functional characteristics of human-system interfaces (HSIs). Because these guidelines only address the HFE aspects of design and not other related considerations, such as instrumentation and control and structural design, they are referred to as HFE guidelines. In addition to the review of actual HSIs, the NRC staff can use the NUREG-0700 guidelines to evaluate a design-specific HFE guidelines document or style guide. The HFE guidelines are organized into four basic parts, which are divided into sections. Part I contains guidelines for the basic HSI elements: information displays, user-interface interaction and management, and analog displays and controls. These elements are used as building blocks to develop HSI systems to serve specific functions. Part II contains the guidelines for reviewing the following HSI systems: alarm system, safety parameter display system, group-view display system, soft control system, computer-based procedure system, automation system, and communication system. Part III provides guidelines for the review of workstations and workplaces. Part IV provides guidelines for the review of HSI support (i.e., maintainability of digital systems and degraded HSI and instrumentation and control conditions).
Software was developed for a Fujitsu HOAP-2 humanoid robot to demonstrate that such "human form" robots can be used to perform useful tasks in an unknown environment; specifically, that they can operate with or in the place of humans to carry out construction operations necessary for space exploration, such as building or maintaining planetary surface habitats for humans. This paper describes the autonomous vision and hand-eye coordination software that enables the HOAP-2 to locate and manipulate objects. Simple vision and pattern detection algorithms including color filtering, noise filtering, image segmentation, orientation filters, and a feedback controlled tracking system enable the robot to locate marked building materials in the workspace. Experimentally determined spatial mappings associate locations in the visual field with the arm joint angles and trajectories necessary to reach these locations, allowing the robot to reach for and manipulate the building materials. These capabilities, when combined with locomotion capabilities, enable the robot to operate autonomously in an unknown workspace.
Thermal end uses dominate building energy consumption and are a major driver of peak demand. As heating is electrified, peak electrical power required will surge, prompting a need for innovative HVAC system designs and controls.These designs must incorporate novel technologies at the component level and new integration techniques at the system level. One such possibility involves the addition of thermal energy storage (TES) in heating and cooling equipment using a phase change material (PCM) heat exchanger. Here, thermal energy storage via phase change can be used to shift the HVAC system loads to times of lower electricity cost, reduced carbon intensity, and greater energy efficiency. Most of the current utilization of PCM in buildings involves passive components. By actively controlling when heat is stored and released from PCM, we can optimize the building HVAC system to cost-effectively meet consumer needs with the flexibility to draw on renewable energy resources when they are abundant and available. While this combination of technologies is promising in theory, simulation-based evaluation of a prototype can be difficult due to the modeling requirements at the component level and the large number of possible configurations and operating modes at the system level. To conduct this evaluation, we use the Modelica language for modeling and simulation because it enables users to represent the important physics of the problem, interchange and rearrange components in an efficient manner, and implement a range of control configurations. In this work, we considered three case studies: a portable building, a large commercial retail store, and a multifamily residential apartment unit. Each of these employs a different system design, ranging from a single package vertical unit incorporating PCM to a central plant with independent heat pump, evaporative cooling, and thermal energy storage components. This paper describes the technologies in question, presents modeling at the component and system levels, and demonstrates building energy and demand charge cost savings with local time-of-use tariffs in a hot-dry climate.
Best practice control sequences are often not implemented correctly, or are not implemented at all, in large commercial buildings. This typically leads to 10-30 percent energy waste, along with reduced occupant productivity and unnecessary equipment wear. The current process of designing and implementing such control sequences is a manual process that starts with designers who often don’t have adequate training, then requires controls programmers to interpret and program a verbose written sequence. This process has been shown to fail to deliver high performance control sequences at scale. The Open Building Control project digitizes the current control delivery process. The project is developing tools for system designers to select control sequences, assess their energy performance and load flexibility potential using whole building simulation, specify the sequence for implementation using machine-to-machine translation by a control provider and formally testing the as-installed sequences by a commissioning agent. The project developed tools for each stage of this delivery process. The key innovation of the project is the development of the Control Description Language, a language that allows such a digitized control delivery process with end-to-end verification. Libraries of control sequences have been implemented using the Control Description Language, and their performance has been demonstrated using whole building energy simulation. An automated translation of such sequences to a commercial control product line has been conducted using a prototype translator. Tools for formal verification of as-installed control sequences relative to their specification have been developed and demonstrated. The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) started the process of forming a committee to make this language an ASHRAE/ANSI Standard. This new standard will complement existing and emerging ASHRAE standards for building communication and semantic modeling by providing a standard for expressing the control logic - the actual brain of the building. We expect this language and the process it enables to be an important contribution to the deployment of high performance building control sequences at scale because it allows taming the complexity of the control delivery process, which is continually increasing due to the need for higher performance and increased load flexibility to meet goals for net zero energy and increased renewable integration.
At the heart of any intelligent flight control system, there is a knowledge based expert system. The efficiency of these knowledge bases is one of the major factors in the success of aviation and space control systems. In the future, the speed and the capabilities of the expert system and their underlying data base(s) will be the limiting factors in the ability to build more accurate real time space controllers. A methodology is proposed for design and construction of such expert systems. It is noted that existing expert systems are inefficient (slow) in dealing with nontrivial real world situations that involve a vast collection of data. However, current data bases, which are fast in handling large amounts of data, cannot carry out intelligent tasks normally expected from an expert system. The system presented provides the power of deduction (reasoning) along with the efficient mechanisms for management of large data bases. In the system, both straight forward evaluation procedures and sophisticated inference mechanisms coexist. The design methodology is based on mathematics and logic, which ensures the correctness of the final product.
Plug and process loads (PPLs) account for a large portion of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering, and data storage. A laboratory proof of concept (PoC) demonstrated all but the energy metering capability, and these capabilities were validated using a series of system tests. The PoC was able to identify when a device was plugged into an outlet and the location of the device in the building. When a device was moved, the PoC's dashboard and database were automatically updated with the new location. The PoC implemented controls to devices from the system dashboard so that devices maintained correct schedules regardless of where they were plugged in within the building. ATLIS's primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. An ATLIS-based system could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.
Cooling towers are an integral component of many refrigeration systems, providing comfort or process cooling across a broad range of applications. They are the point in the system where heat is dissipated to the atmosphere through the evaporative cooling process. Cooling towers are commonly found in industrial applications and are also often used in water-cooled chilled water plants in medium to large commercial buildings. Continuous monitoring and partial water softening for cooling towers used in medium to large commercial buildings are the focus of this paper. Cooling towers consume large amounts of water. Cooling tower-related water consumption is one of largest potable water loads within buildings in the United States, with substantial building water use associated with heating and cooling. Regional water shortages have highlighted a need to reduce water consumption; the U.S. General Services Administration (GSA) and Executive Order 13834 place priority on reducing water consumption. This priority has fueled interest in the identification, investigation, and potential broad deployment of cost-effective opportunities to reduce water use, such as alternative water treatment (AWT) technologies for cooling towers. Traditional water treatment approaches use chemicals to extend the ability of the water to hold scaling minerals in suspension, minimize corrosion, and prevent biological growth. This treatment protects the chillers and cooling tower equipment; however, even when chemicals are used regularly, a certain percentage of condenser water must be drained and made up with fresh water to maintain system water quality parameters. In addition, the use of chemicals sometimes creates a waste disposal issue and can cause building owners to incur additional fees, such as disposal or wastewater charges. To manage cooling tower water treatment, GSA typically contracts with a company specializing in conventional chemical maintenance for a fixed fee. While there are many types and vendors of AWT systems, this project assesses the effectiveness of one technology provided by Aqualogix. This system is a chilled water plant monitoring and control system aimed at optimizing system performance by reducing the blowdown occurrences used to remove mineral build-up. The technology consists of two components – continuous programmable logic control (PLC) monitoring and side-stream filtration with partial water softening. PLC monitoring calculates cycles of concentration (CoC) and determines the optimum amount of blowdown water required to satisfy all water chemistry requirements. Side-stream filtration removes suspended matter and improves biocide efficacy while precisely dispensing softened water to achieve optimal makeup water hardness. Unlike other AWT systems evaluated by GSA to date, this system does not replace the legacy treatment system but is used in addition to chemical water treatment. The vendor claims their technology will reduce water consumption, water discharge, and maintenance costs. The AWT system evaluated in this demonstration is a commercialized technology. Given its commercialized state, the system evaluated in this report is at a Technology Readiness Level 9 according to National Aeronautics and Space Administration (NASA) definitions.
Machine learning proxy models are often used to speed up or completely replace complex computational models. The greatly reduced and deterministic computational costs enable new use cases such as digital twin control systems and global optimization. The challenge of building these proxy models is generating the training data. A naive uniform sampling of the input space can result in a non-uniform sampling of the output space of a model. This can cause gaps in the training data coverage that can miss finer scale details resulting in poor accuracy. While larger and larger data sets could eventually fill in these gaps, the computational burden of full-scale simulation codes can make this prohibitive. In this paper, we present an adaptive data generation method that utilizes uncertainty estimation to identify regions where training data should be augmented. By targeting data generation to areas of need, representative data sets can be generated efficiently. The effectiveness of this method will be demonstrated on a simple one-dimensional function and a complex multidimensional physics model.
SAND2024-16910O FIREWHEEL is a tool for experiment orchestration that assists a user in building and controlling repeatable experiments of distributed network systems at any scale. This version also includes FIREWHEEL v2.7 and its associated companion model components. With FIREWHEEL, users can easily construct modular parts of a cyber system, called Model Components. The Model Components can be combined to form an experiment. Most experiments are then instantiated using an emulation tool, such as minimega.
It features a framework of a firmware and software architecture in support of building a digital low-level RF control system for accelerators, where precised digital RF generation and measurement are needed across many RF channels. It primarily supports the Xilinx RFSoC chips (xczu48dr, xczu47dr, xczu29dr) and their evaluation boards (zcu208, zcu216), for a highly integrated solution enabling the need for synchronous low-level RF systems, including: multi-tile synchronization, external reference for sampling clocks, deterministic delay, aligned NCO phase for digital mixers, and built-in EPICS IOC.
Building-level microgrids may be a key strategy to unlock the combined potential of flexible loads, renewable generation, and energy storage. However, few software options exist for integrated control of building loads and other distributed energy resources at this scale. The commercial software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice. The SolarPlus Optimizer (SPO) is an open-source building-level microgrid control platform that uses Model Predictive Control to optimize both building loads and behind-the-meter energy storage to reduce energy bills and increase demand flexibility. This paper evaluates the capabilities of SPO in a small commercial building in Northern California under multiple electricity tariffs and demand response scenarios. Comparing SPO operation with an emulated battery and baseline operation employing a commercial optimization service, SPO reduced electricity bills by an estimated 7.3% in summer, 3.2% in spring, and 3.7% in winter. In a “load shape” scenario meant to counter the “duck curve”, SPO achieved 71% fewer violations from the load signal than the baseline control method. During a three hour long load shed event, SPO reduced cooling and refrigeration load by 38%. This research shows significant potential to provide load flexibility for building-level microgrids for this type of control systems. Finally, the paper discusses the future direction of research on open-source control systems.
A new generation of sensor rich, massively distributed, autonomous systems are being developed that have the potential for profound social, environmental, and economic change. These include networked building energy systems, autonomous space probes, chemical plant control systems, satellite constellations for remote ecosystem monitoring, power grids, biosphere-like life support systems, and reconfigurable traffic systems, to highlight but a few. To achieve high performance, these immobile robots (or immobots) will need to develop sophisticated regulatory and immune systems that accurately and robustly control their complex internal functions. To accomplish this, immobots will exploit a vast nervous system of sensors to model themselves and their environment on a grand scale. They will use these models to dramatically reconfigure themselves in order to survive decades of autonomous operations. Achieving these large scale modeling and configuration tasks will require a tight coupling between the higher level coordination function provided by symbolic reasoning, and the lower level autonomic processes of adaptive estimation and control. To be economically viable they will need to be programmable purely through high level compositional models. Self modeling and self configuration, coordinating autonomic functions through symbolic reasoning, and compositional, model-based programming are the three key elements of a model-based autonomous systems architecture that is taking us into the New Millennium.
Marshall Space Flight Center’s Test Stand 115 (TS115) is a propulsion component test facility in operation since its original activation in 1964 for testing small to medium size liquid rocket engine components including injectors, channel-cooled chambers, nozzles, passively-cooled metallic and composite nozzle extensions, valves, turbomachinery, and igniters. TS115 is a "blowdown" type facility, using high pressure tankage and components to provide liquid, gaseous, and cryogenic fluid delivery at specified pressures and flowrates. The facility consists of an open steel test stand structure, a mechanical hardware preparation shop, an electrical support equipment building, a control room, and a centralized data system room. In general, the facility infrastructure is rated to 3,000 psig. TS115 can accommodate thrust levels up to 10,000 lbf in the horizontal position. The facility is actively used for various internal NASA test programs as well as test campaigns for external customers from other government agencies, commercial industry partners, and academia. The available fluid systems, electrical power and instrumentation capabilities, facility controls and data acquisition systems, test program support capabilities, and available test rig configurations for external customer use are discussed in this paper.
This paper describes the design of a model-based autonomous planning system that will enable robots to manage a space-borne chemical laboratory. In a model-based planning system, knowledge is encapsulated in the form of models at the various layers to support the predefined system objectives. Thus the model-based approach can be considered as an extended planning paradigm which is able to base its planning, control, diagnosis, repair, and other activities on a variety of objectives-related models. A System Entity Structure/Model Base framework is employed to support autonomous system design through the ability to generate a family of planning alternatives as well as to build hierarchical event-based control structures. The model base is a multilevel, multiabstraction, and multiformalism system organized through the use of system morphisms to integrate related models.