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DOE OSTI2021

U.S. Industrial and Commercial Motor System Market Assessment Report Volume 1: Characteristics of the Installed Base

Motor systems are an integral part of our industrial and commercial facilities. They provide the motive force behind the fans, pumps, compressors, chillers, and conveyors in these facilities. Given their centrality to any facility’s operations, they are a critical energy end use to understand, particularly when developing technologies and policies to meet sustainability goals, improve productivity, and enhance resilience. In the late 1990s, the U.S. Department of Energy (DOE) conducted two seminal studies to better understand the installed stock and energy savings opportunities of industrial and commercial motor systems. In the industrial sector, The United States Industrial Electric Motor Systems Market Opportunities Assessment used primary data collected through onsite assessments and led to a greater understanding of the installed base of motor systems, their characteristics, and the opportunities for energy savings (U.S. Department of Energy, 2002). Notable findings included the following: Industrial motor systems consumed 679 billion kilowatt-hours (kWh) in 1994, representing 23 percent of U.S. electricity consumption. Cost-effective energy efficiency measures could result in 62-104 billion kWh of energy savings annually. Sixty-two percent of the energy savings potential was from fan, pump, and compressor end use equipment. Nearly half of motor system electricity consumption was attributable to approximately 3,500 facilities, or 1.5 percent of U.S. manufacturing facilities. Opportunities for Energy Savings in the Residential and Commercial Sectors with High Efficiency Electric Motors provided an evaluation of the installed stock of motor driven equipment in U.S. commercial and residential buildings and opportunities for utilization of high efficiency motors and variable speed technologies (Arthur D. Little, 1999). Notable findings included the following: Commercial motor systems consumed 343 billion kWh in 1995, with refrigeration and space conditioning constituting 93 percent of the total. Cost-effective energy efficiency measures could result in 51 billion kWh of energy savings annually. Due in no small part to these seminal studies, motor system technologies and usage characteristics have changed drastically since the late 1990s. Greater awareness of cost-effective strategies for reducing motor system electricity consumption have been developed and deployed. This includes several software tools, literature, and utility and government programs promoting energy efficiency improvements in motor driven systems. Additionally, several rounds of energy efficiency standards have been enacted, resulting in improved installed motor efficiency. The cost of variable speed drives has dropped substantially, and combined with utility rebate programs, has led to their greater adoption. Further, since these results were published, the U.S. manufacturing sector has undergone a massive transformation. Due to global competition, some sectors have relocated operations overseas. Others have brought operations onshore to avail low cost and abundant natural gas. Additionally, automation and robotics have pervaded the entire sector. Consequently, these two reports likely do not represent the current state of motor driven systems in U.S. industrial and commercial facilities. As cited in recent studies, the lack of current information on motor system electricity consumption and use characteristics limits the ability to conduct analysis on energy savings potential, develop technologies to address energy and productivity gaps, and develop programs to promote energy efficiency practices and technologies for motor systems (International Energy Agency, 2007; UNIDO, 2010; McKane and Hasanbeigi, 2011; Waide and Brunner, 2011). Specifically, the lack of information affects a range of stakeholders: Governments must rely on outdated information when setting research agendas, developing policies, and designing energy efficiency programs and offerings. Utilities and energy efficiency programs cannot identify the current market needs or potential impact when designing rebate and energy efficiency programs. Electric grid planners cannot identify motor system usage characteristics when developing plans to support the resilience of the electric grid. Manufacturers of motors, motor driven equipment, and drives are hampered when developing technologies to meet the needs of their market. Motor system end users are limited in their ability to identify energy saving opportunities within their own facilities because they do not have reliable benchmark information. In response to the lack of current information and analysis on industrial and commercial motor systems, the DOE initiated an update to these two studies. Launched in 2016 and led by Lawrence Berkeley National Laboratory (LBNL), the Motor System Market Assessment (MSMA) provides an updated, more comprehensive assessment of the installed stock of motor systems in both the industrial and commercial sectors, a review of the supply chains supporting motor and drives in the U.S., and the performance improvement opportunity available from using best available technologies and maintenance and operation practices. The outcomes of the MSMA are documented in three U.S. Industrial and Commercial Motor System Market Assessment reports, with this report being the first listed: 1. Volume 1: Characteristics of the Installed Base (this report) documents the findings on the installed base of motor systems in the U.S. industrial and commercial sectors. Quantification of energy savings potential is not documented in this report but in Volume 3. 2. Volume 2: Motors and Drives Supply Chain Review reviews the state of supply chains for motors and drives installed in U.S. industrial and commercial facilities, focusing on advanced motor and drive technologies and their constituent materials. 3. Volume 3: Energy Savings Opportunity analyzes the energy performance improvement opportunity for the installed base of U.S. industrial and commercial motor systems. This report has been prepared as a reference for motor system stakeholders. It provides factual information as could be best determined by the assessment results and avoids speculating on any findings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Powering ≈50 µm Motion by a Molecular Event in DNA Crystals

A major challenge in material design is to couple nanoscale molecular and supramolecular events into desired chemical, physical, and mechanical properties at the macroscopic scale. Here, a novel self-assembled DNA crystal actuator is reported, which has reversible, directional expansion and contraction for over 50 μm in response to versatile stimuli, including temperature, ionic strength, pH, and redox potential. The macroscopic actuation is powered by cooperative dissociation or cohesion of thousands of DNA sticky ends at the designed crystal contacts. The increase in crystal porosity and cavity in the expanded state dramatically enhances the crystal capability to accommodate/encapsulate nanoparticles/proteins, while the contraction enables a “sponge squeezing” motion for releasing nanoparticles. This crystal actuator is envisioned to be useful for a wide range of applications, including powering self-propelled robotics, sensing subtle environmental changes, constructing functional hybrid materials, and working in drug controlled-release systems.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Chemical pumps and flexible sheets spontaneously form self-regulating oscillators in solution

The synchronization of self-oscillating systems is vital to various biological functions, from the coordinated contraction of heart muscle to the self-organization of slime molds. Through modeling, we design bioinspired materials systems that spontaneously form shape-changing self-oscillators, which communicate to synchronize both their temporal and spatial behavior. Here, catalytic reactions at the bottom of a fluid-filled chamber and on mobile, flexible sheets generate the energy to “pump” the surrounding fluid, which also transports the immersed sheets. The sheets exert a force on the fluid that modifies the flow, which in turn affects the shape and movement of the flexible sheets. This feedback enables a single coated (active) and even an uncoated (passive) sheet to undergo self-oscillation, displaying different oscillatory modes with increases in the catalytic reaction rate. Two sheets (active or passive) introduce excluded volume, steric interactions. This distinctive combination of the hydrodynamic, fluid–structure, and steric interactions causes the sheets to form coupled oscillators, whose motion is synchronized in time and space. We develop a heuristic model that rationalizes this behavior. These coupled self-oscillators exhibit rich and tunable phase dynamics, which depends on the sheets’ initial placement, coverage by catalyst and relative size. Moreover, through variations in the reactant concentration, the system can switch between the different oscillatory modes. This breadth of dynamic behavior expands the functionality of the coupled oscillators, enabling soft robots to display a variety of self-sustained, self-regulating moves.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Embedded Fluidic Sensing and Control with Soft Open‐Cell Foams

Abstract The synthesis of soft matter intelligence with circuit‐driven logic has enabled a new class of robots that perform complex tasks or conform to specialized form factors in unique ways that cannot be realized through conventional designs. Translating this hybrid approach to fluidic systems, the present work addresses the need for sheet‐based circuit materials by leveraging the innate porosity of foam—a soft material—to develop pneumatic components that support digital logic, mixed‐signal control, and analog force sensing in wearables and soft robots. Analytical tools and experimental techniques developed in this work serve to elucidate compressible gas flow through porous sheets, and to inform the design of centimeter‐sized foam resistors with fluidic resistances on the order of 10 9 Pa s m −3 . When embedded inside soft robots and wearables, these resistors facilitate diverse functionalities spanning both sensing and control domains, including digital logic using textile logic gates, digital‐to‐analog signal conversion using ladder networks, and analog sensing of forces up to 40 N via compression‐induced changes in resistance. By combining features of both circuit‐based and materials‐based approaches, foam‐enabled fluidic circuits serve as a useful paradigm for future hybrid robotic architectures that fully embody the sensing and computing capabilities of soft fluidic materials.

Rajappan, Anoop↗

DOE OSTI2022

Programmable soft valves for digital and analog control

In soft devices, complex actuation sequences and precise force control typically require hard electronic valves and microcontrollers. Existing designs for entirely soft pneumatic control systems are capable of either digital or analog operation, but not both, and are limited by speed of actuation, range of pressure, time required for fabrication, or loss of power through pull-down resistors. Using the nonlinear mechanics intrinsic to structures composed of soft materials—in this case, by leveraging membrane inversion and tube kinking—two modular soft components are developed: a piston actuator and a bistable pneumatic switch. These two components combine to create valves capable of analog pressure regulation, simplified digital logic, controlled oscillation, nonvolatile memory storage, linear actuation, and interfacing with human users in both digital and analog formats. Three demonstrations showcase the capabilities of systems constructed from these valves: 1) a wearable glove capable of analog control of a soft artificial robotic hand based on input from a human user’s fingers, 2) a human-controlled cushion matrix designed for use in medical care, and 3) an untethered robot which travels a distance dynamically programmed at the time of operation to retrieve an object. This work illustrates pathways for complementary digital and analog control of soft robots using a unified valve design.

42 ENGINEERING↗

DOE OSTI2025

Mineralized sclerites in the gorgonian coral Leptogorgia chilensis as a natural jamming system

The soft corals (Cnidaria, Octocorallia), a diverse group of colonial marine invertebrates, can reversibly tune their body stiffness in response to external stimuli. This capability is attributed to their dynamic skeletal systems, which consist of thousands of mineralized skeletal elements, called sclerites, embedded within a gel-like matrix that swells/deswells and unjams/jams the sclerites, thus modulating skeletal stiffness. While sclerite morphology is widely used for species identification, its role in the mechanical performance of a soft coral’s skeletal system is largely unknown. Here, we investigated structure-jamming relationships in sclerite-based skeletal architectures using the red gorgonian octocoral Leptogorgia chilensis as a model system. The sclerites of L. chilensis exhibit a shaft-like geometry with two axial branches and two sets of triradiate side branches, which are aligned with the crystallographic symmetry of the constituent magnesium-containing calcite. By combining multiscale three-dimensional (3D) structural characterization, parametric geometrical modeling, 3D printing, mechanical testing, and discrete element simulations, we demonstrate how sclerite geometry achieves a balanced jamming performance in terms of stiffness, weight, strength, and fracture resistance in comparison to alternative geometries parametrically modified from the native sclerites (e.g., changes in the length and number of side branches). Here, we also found that these performance metrics are achieved through the effective interlocking among side and axial branches, which is further enhanced by the fractal-like microscopic spikes on the branch tips. The findings in this natural jamming system offer insights for designing synthetic mechanotunable material architectures for a wide range of applications, from soft robotics to mechanical dampeners.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Methods, systems, and devices relating to surgical end effectors

The embodiments disclosed herein relate to various medical device components, including components that can be incorporated into robotic and/or in vivo medical devices, and more specifically including end effectors that can be incorporated into such devices. Certain end effector embodiments include various vessel cautery devices that have rotational movement as well as cautery and cutting functions while maintaining a relatively compact structure. Other end effector embodiments include various end effector devices that have more than one end effector.

42 ENGINEERING↗

DOE OSTI2024

Energy digital twins in smart manufacturing systems: A case study

Not provided.

Computer Science↗

DOE OSTI2022

Designing, synthesizing, and modeling active fluids

We review recent advances in the design, synthesis, and modeling of active fluids. Active fluids have been at the center of many technological innovations and theoretical advances over the past two decades. Research on this new class of fluids has been inspired by the fascinating and remarkably efficient strategies that biological systems employ, leading to the development of biomimetic nano- and micro-machines and swimmers. The review encompasses active fluids on both the nano- and micro-scale. We start with examples of biological active systems before we discuss how experimentalists leverage novel propulsion mechanisms to power nano- and micro-machines. Furthermore, we then examine how the study of these far-from-equilibrium systems has prompted the development of new simulation methods and theoretical models in nonequilibrium physics to account for their mechanical, thermodynamic, and emergent properties. Recent advances in the field have paved the way for the design, synthesis, and modeling of autonomous systems at the nano- and micro-scale and opened the door to the development of soft matter robotics.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Robotics for Energy Infrastructure Construction on Earth and Beyond: Pilot Study Exploring Level 3-4 Semi-Autonomous Installation of a Reduced-Scale Photovoltaic Power Plant Prototype: Preprint

There is a growing need to build energy infrastructure at massive scale on both Earth and in space. On Earth, increasing electricity demand from applications such as AI data centers is driving rapid expansion of power systems, while in space, long-duration missions such as lunar operations require reliable and resilient energy infrastructure that can be deployed quickly. These needs outpace the capabilities of conventional construction methods. Robotic construction offers a path to faster, lower-cost, and more consistent deployment, yet most existing approaches focus on automating individual tasks rather than end-to-end assembly. The Industrialized Construction Innovation (ICI) team at the National Laboratory of the Rockies (NLR), in collaboration with the Colorado School of Mines, has been investigating robotics and automation strategies for rapid end-to-end energy infrastructure construction. This paper presents a pilot study demonstrating level 3-4 semi-autonomous, end-to-end robotic assembly of a reduced-scale photovoltaic power plant prototype under terrestrial conditions. The approach combines hardware redesign of photovoltaic components for robotic compatibility, discrete-event and physics-based robotic simulations in synthetic environments, and sim-to-real deployment to execute end-to-end robotic assembly of[NM1.1][NM1.2] tracking components, structural members, photovoltaic modules, and embedded electrical connections. The pilot identifies key limitations like tolerance management, perception and localization, end effector capability, fastening methods, and multi-physics simulation fidelity, that must be addressed to enable end-to-end robotic assembly of full-scale energy infrastructure. The study highlights how these insights inform scaling strategies for terrestrial energy infrastructure and adaptation to unstructured and extreme environments, including off-world scenarios such as robotic assembly of vertical tall lunar towers.

14 SOLAR ENERGY↗

DOE OSTI2020

On-the-fly closed-loop materials discovery via Bayesian active learning

Active learning—the field of machine learning (ML) dedicated to optimal experiment design—has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics. In this work, we focus a closed-loop, active learning-driven autonomous system on another major challenge, the discovery of advanced materials against the exceedingly complex synthesis-processes-structure-property landscape. We demonstrate an autonomous materials discovery methodology for functional inorganic compounds which allow scientists to fail smarter, learn faster, and spend less resources in their studies, while simultaneously improving trust in scientific results and machine learning tools. This robot science enables science-over-the-network, reducing the economic impact of scientists being physically separated from their labs. The real-time closed-loop, autonomous system for materials exploration and optimization (CAMEO) is implemented at the synchrotron beamline to accelerate the interconnected tasks of phase mapping and property optimization, with each cycle taking seconds to minutes. We also demonstrate an embodiment of human-machine interaction, where human-in-the-loop is called to play a contributing role within each cycle. This work has resulted in the discovery of a novel epitaxial nanocomposite phase-change memory material.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Reinforcement learning building control approach harnessing imitation learning

Reinforcement learning (RL) has shown significant success in sequential decision making in fields like autonomous vehicles, robotics, marketing and gaming industries. This success has attracted the attention to the RL control approach for building energy systems which are becoming complicated due to the need to optimize for multiple, potentially conflicting, goals like occupant comfort, energy use and grid interactivity. However, for real world applications, RL has several drawbacks like requiring large training data and time, and unstable control behavior during the early exploration process making it infeasible for an application directly to building control tasks. To address these issues, an imitation learning approach is utilized herein where the RL agents starts with a policy transferred from accepted rule based policies and heuristic policies. This approach is successful in reducing the training time, preventing the unstable early exploration behavior and improving upon an accepted rule-based policy - all of these make RL a more practical control approach for real world applications in the domain of building controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Automated tracking of prefabricated components for areal-time evaluator to optimize and automateinstallation

Trade associations for prefabricated construction estimate that about 50% of prefabricated wall projects have alignment problems that lead to defects and rework. Additionally, component installation times average between 30 and 60 minutes per component. To address these issues, a real-time evaluator (RTE) system was introduced to decrease cost and automate prefabricated component installation by reducing the installation time, decreasing rework, and enhancing energy performance through higher installation quality. The RTE uses commonly available hardware and software to perform autonomous tracking to measure the real-time location and orientation of components as they are crane-lifted and installed. The hardware, software, and algorithms that allow the autonomous tracking of components are detailed. An algorithm to automate the initial search for a component with three attached retroreflectors is proposed. Algorithms to automate the measurement of component position and orientation are also proposed. Simple lab-scale proof-of-concept experiments were conducted to assess the algorithms for automation of component searching, measurement of real-time movement, and measurement of component orientation. With additional development, the system can be used as a tool to generate the commands for autonomous crane operation or single-task construction robots.

Hayes, Nolan↗

DOE OSTI2022

Flexible Siting Criteria and Staff Minimization for Micro-Reactors

The economic potential of micro-reactors is vast and underestimated. Commonly-emphasized applications include niche markets such as remote communities, mines and military bases. However, micro-reactors could be used as flexible energy generators also for larger markets, such as mobile and containerized agriculture and manufacturing facilities, district heating, micro-grids for data centers, sea ports, airports and hospitals. The implication is that micro-reactors may have to be deployed also in non-remote locations. Successful implementation of micro-reactors needs a navigable and predictable licensing process, technology-appropriate siting restrictions, risk-informed emergency and safety requirements, and practical operating and maintenance requirements. The primary goal of this project was to develop siting criteria that are tailored to micro-reactors deployable in densely-populated areas, e.g., urban environments. To achieve that goal, we compared the characteristics of the MIT research reactor (MITR) with those of leading micro-reactor concepts (e.g., eVinci, USNC, Aurora), and evaluated whether and how the MITR design basis (e.g., inherent safety features, engineered safety systems, source term, emergency planning and emergency operating procedures) and associated regulations may be applicable to these new micro-reactors as well. What makes MITR a unique analogue in this context is its small power rating (6 MWt) and physical size, mode of operations (24/7 with a somewhat more commercial flavor than typical university reactors), and especially its urban location. Of course significant differences exist, such as mission (power production vs. research) and the reactor design itself. Leveraging the MITR experience, this project was able to generate criteria that will allow micro-reactors to realize their full economic potential as flexible heat and electricity generators for a diverse portfolio of applications in non-remote locations. As such, the outcome of this project might encourage investment in and use of micro-reactors. A second goal of the project was to conceptualize a model of operations for micro-reactors that would minimize the staffing requirements, and thus reduce the cost of electricity and heat generated by these systems. Here too our approach was to systematically review the MITR experience and requirements, as well as survey the innovations in autonomous control technologies and monitoring (e.g., advanced sensors, drones, robotics, AI) that would permit a dramatic reduction in staffing at future micro-reactor installations. The scope of work was expanded after the start date to include also an evaluation of micro-reactor security, using the so-called consequence-based analysis, and the development of a methodology to perform dynamic risk assessment for micro-reactors, using system theory and modeling and simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Powering the Blue Economy: Economics of Marine Renewable Energy Systems

This presentation, part of the Policy and Innovation Drivers Shaping the Market for Marine Renewable Energy panel of the 2020 Marine Renewable Energy Conference: On and Off the Grid, moderated by Leslie-Ann McGee, Assistant Director of the Consortium for Marine Robotics at the Woods Hole Oceanographic Institution and Program Manager, Cape Cod Blue Economy Foundation, delves into government policies incentivizing technological advances, collaborative models for technology development, market trends, and permitting hurdles. Panelists include: Jennifer Garson, Senior Advisor, U.S. Dept. of Energy Lead for the Powering the Blue Economy Initiative; Henry Jeffrey, Chairman of the Technology Collaboration Programme for Ocean Energy Systems, University of Edinburgh; Alf Carroll, SBIR Blackbelt and Ocean Energy SME, Raytheon Technologies; Walter Schurtenberger, Founder, Hydrokinetic Energy Corp.; and Dale "Scott" Jenne, Engineer, National Renewable Energy Laboratory.

50 EE - Wind and Water Power Program - Water (EE-4↗

DOE OSTI2023

First detection of the BAO signal from early DESI data

We present the first detection of the baryon acoustic oscillations (BAOs) signal obtained using unblinded data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). From a selected sample of 261 291 luminous red galaxies spanning the redshift interval 0.4 < z < 1.1 and covering 1651 square degrees with a 57.9 per cent completeness level, we report a ∼5σ level BAO detection and the measurement of the BAO location at a precision of 1.7 per cent. Using a bright galaxy sample of 109 523 galaxies in the redshift range 0.1 < z < 0.5, over 3677 square degrees with a 50.0 per cent completeness, we also detect the BAO feature at ∼3σ significance with a 2.6 per cent precision. These first BAO measurements represent an important milestone, acting as a quality control on the optimal performance of the complex robotically actuated, fibre-fed DESI spectrograph, as well as an early validation of the DESI spectroscopic pipeline and data management system. Based on these first promising results, we forecast that DESI is on target to achieve a high-significance BAO detection at sub-per cent precision with the completed 5-yr survey data, meeting the top-level science requirements on BAO measurements. This exquisite level of precision will set new standards in cosmology and confirm DESI as the most competitive BAO experiment for the remainder of this decade.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Model-Based Ultrasonic Signal Processing for the Nondestructive Evaluation of Additive Manufacturing Components

42 ENGINEERING↗

DOE OSTI2021

Time-of-Flight Estimation for Nondestructive Evaluation

Ultrasonic testing (UT) for nondestructive evaluation (NDE) is a critical entity necessary to resolve both the quality and precision questions of complex parts evolving from the classical approaches to the innovative additive manufacturing (AM) process. This modality provides the essential quantitative information for acceptance and potential flaw detectionof apart under investigation. A primary ingredient in UT besides the required precision robotic hardware for theacquisition of high-qualitymeasurement data is the underlying signal processing. It is here that much of the system performance capability resides. In this report,we discuss the basic steps in UT signal processing along with current capabilities that must be achieved in order to satisfy the criticaldemands of the various LLNL programs.In itsbasic foundations, signal processing is essentially the “extraction of critical information (signals) from noisy, uncertain data.” Clearly, in a perfect world the best signal processing is none---just make a reliable, noise-free, uncertainty-free, measurement. Unfortunately, even the best of systems is still straddled within the confines and limitations of physical instrumentation. With this in mind, we discuss the development of signal processing techniques toextract the desired UT information from noisy measurement data. We start with a discussion of a simple homogeneous representation of a “part” under investigation and its insonification by an ultrasonicexcitation from a physics-based perspective. Once developed, we briefly discussthe various choices of excitation signals and their tradeoffs.Next,we discuss a simulation approach employing simple models from the signal processing perspective and then move on to the development of the basic signal processing approach to ultrasonic signal processing all based on estimating the pulse arrival estimation. Starting with simple peak detection techniques, progressing to the processing workhorse so-called “matched-filter” and finally to the more sophisticated “model-based matched filter.”The underlying pre-and post-processing of noisy measurement data along with the application of these techniques are subsequently demonstrated on experimental ultrasonic data.Finally, we present some results for processing “weld” data when the ultrasonic excitation signal is not directly available.

42 ENGINEERING↗