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DOE OSTI2021

Revisit the Scalability of Deep Auto-Regressive Models for Graph Generation

As a new promising approach to graph generations, deep auto-regressive graph generation has drawn increasing attention. It however has been commonly deemed as hard to scale up to work with large graphs. In existing studies, it is perceived that the consideration of the full non-local graph dependences is indispensable for this approach to work, which entails the needs for keeping the entire graph’s info in memory and hence the perceived “inherent” scalability limitation of the approach. This paper revisits the common perception. It proposes three ways to relax the dependences and conducts a series of empirical measurements. It concludes that the perceived “inherent” scalability limitation is a misperception; with the right design and implementation, deep auto-regressive graph generation can be applied to graphs much larger than the device memory. The rectified perception removes a fundamental barrier for this approach to meet practical needs.

Yang, Shuai↗

DOE OSTI2020

Simulating the Autonomous Future: A Look at Virtual Vehicle Environments and How to Validate Simulation Using Public Data Sets

The rapid evolution of autonomous vehicles (AVs) has exposed the need for fast-paced development and testing processes of a variety of perception, planning, and control algorithms. To expedite development, the AV industry and researchers leverage virtual vehicle environments to simulate a range of test scenarios that may otherwise be costly or difficult to conduct on a real test track. However, the various virtual environments may have different results depending on the fidelity of various simulation features, such as vehicle dynamics, sensor simulation, and environment recreation. Herein, this tutorial article examines a proposed framework for constructing, parameterizing, and validating a virtual vehicle environment using an existing AV data set. First, an overview of several open source and commercially available simulation tools, including their associated workflows, for scene and scenario creation is presented. Next, various open AV data sets are examined to inform the data set selection for the validation framework. Then, an example workflow of recreating a real-world scene from the selected data set in a simulation tool with various emulated sensors parameterized to match the data set is demonstrated. Finally, an example AV-perception algorithm is subjected to data streams from virtual and real-world environments and suggested metrics for analyzing the results are discussed.

42 ENGINEERING↗

DOE OSTI2023

A Comparative Study of the Perceptual Sensitivity of Topological Visualizations to Feature Variations

Color maps are a commonly used visualization technique in which data are mapped to optical properties, e.g., color or opacity. Color maps, however, do not explicitly convey structures (e.g., positions and scale of features) within data. Topology-based visualizations reveal and explicitly communicate structures underlying data. Although our understanding of what types of features are captured by topological visualizations is good, our understanding of people's perception of those features is not. Further, this paper evaluates the sensitivity of topology-based isocontour, Reeb graph, and persistence diagram visualizations compared to a reference color map visualization for synthetically generated scalar fields on 2-manifold triangular meshes embedded in 3D. In particular, we built and ran a human-subject study that evaluated the perception of data features characterized by Gaussian signals and measured how effectively each visualization technique portrays variations of data features arising from the position and amplitude variation of a mixture of Gaussians. For positional feature variations, the results showed that only the Reeb graph visualization had high sensitivity. For amplitude feature variations, persistence diagrams and color maps demonstrated the highest sensitivity, whereas isocontours showed only weak sensitivity. These results take an important step toward understanding which topology-based tools are best for various data and task scenarios and their effectiveness in conveying topological variations as compared to conventional color mapping.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

C-terminal conformational changes in SCF-D3/MAX2 ubiquitin ligase are required for KAI2-mediated signaling

Karrikins (KARs) are bioactive molecules derived from burning vegetation. Plants perceive KARs through the hydrolase KARRIKIN INSENSITIVE 2 (KAI2) that interacts with the F-box protein ubiquitin ligase MORE AXILLARY GROWTH 2 (MAX2). MAX2 also plays a role in the perception and signal activation by Strigolactone (SL), a phytohormone controlling various developmental processes in plants. SL also acts as a rhizosphere signal to activate arbuscular mycorrhiza fungi that can be exploited by parasitic plants. kai2 knockouts exhibit distinct developmental defects and therefore KAI2 is hypothesized to perceive an unidentified endogenous ligand provisionally termed KAI2-Ligand (KL). Upon KAR/KL perception, the protein complex of KAI2-MAX2 targets SUPPRESSOR OF MAX2-1/2 (SMAX1)/SMXL2 for proteasomal degradation. Despite the identification of the key components KAI2, MAX2, and SMAX1 in KAR/KL signaling, their mode of interaction and regulation remains elusive. Recently, the regulatory function of the conformational switch of MAX2 C-terminal helix (CTH) in SL signaling has been demonstrated however its role in KAR/KL signaling remained unknown. Here we address the function of MAX2-CTH dynamics both in vitro and in planta and show that the central role of CTH is conserved between SL and KAR/KL signaling pathway.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Movement with meaning: integrating information into meta-ecology

Fluxes of matter, energy and information over space and time contribute to ecosystems' functioning and stability. The meta-ecosystem framework addresses the dynamics of ecosystems linked by these fluxes but, to date, has focused solely on energy and matter. Here, we synthesize existing knowledge of information's effects on local and connected ecosystems and demonstrate how new hypotheses emerge from the integration of ecological information into meta-ecosystem theory. First, we begin by defining information and reviewing how it flows among ecosystems to affect connectivity, local ecosystem function and meta-ecosystem dynamics. We focus on the role of semiotic information: that which can reduce an individual's – or a group's – uncertainty about the state of the world. Semiotic information elicits behavioral, developmental and life history responses from organisms, potentially leading to fitness consequences. Organisms' responses to information can ripple through trophic interactions to influence ecosystem processes, their local and regional dynamics, and the spatiotemporal flows of energy and matter, therefore information should affect meta-ecosystem dynamics such as stability and productivity. While specific subdisciplines of ecology currently consider different types of information (e.g. social and cultural information, natural and artificial light or sound, body condition, genotype and phenotype), many ecological models currently account for neither the spatio–temporal distribution of information nor its perception by organisms. We identify the empirical, theoretical and philosophical challenges in developing a robust information meta-ecology and offer ways to overcome them. Finally, we present new hypotheses for how accounting for realistic information perception and responses by organisms could impact processes such as home range formation and spatial insurance, and thus our understanding of ecological dynamics across spatial and temporal scales. Accounting for information will be essential to understanding how dynamics such as fitness, organismal movement and trophic interactions influence meta-ecosystem functioning, and predicting how ecosystem processes are affected by anthropogenic pressures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Impact of Timing in the Design Process on Students’ Application of Design for Additive Manufacturing Heuristics

The goal of this work is to study the way student designers use design for additive manufacturing (DfAM) rules or heuristics. It can be challenging for novice designers to create successful designs for additive manufacturing (AM), due to its recent surge in popularity and lack of formal education or training. A study was carried out to investigate the way novices apply DfAM heuristics when they receive them at different points in the design process. A design problem was presented to students, and three different groups of student participants were given a lecture on DfAM heuristics at three different points in the design process: before the initial design, between the initial design and redesign, and after the redesign. The novelty and quality of each of the resulting designs were evaluated. Results indicate that although the DfAM heuristics lecture had no impact on the overall quality of the designs generated, participants who were given the heuristics lecture after the initial design session produced designs that were better-suited for 3D printing in the second phase of the design activity. However, receiving this additional information appears to prevent students from creatively iterating upon their initial designs, as participants who received heuristic information between the design sessions experienced a decrease in novelty between the two sessions. Additionally, receiving the heuristics lecture increased all students’ perceptions of their ability to perform DfAM-related tasks. Furthermore, these results validate the practicality of design heuristics in lecture form as AM training tools while also emphasizing the importance of iteration in the design process.

computer-aided design↗

DOE OSTI2020

Nurses’ Satisfaction with Patient Room Lighting Conditions: A Study of Nurses in Four Hospitals with Differences in the Environment of Care

Lighting systems in patient rooms must balance energy efficiency concerns with the holistic needs of patients, families, and medical caregivers. This paper reports survey responses from 138 individuals working in medical-surgical units in four hospitals, with three of the hospitals having traditional lighting systems and the other hospital having a more contemporary lighting system. The results add to a growing evidence base on the effects of lighting on nurses’ job performance, job satisfaction, and overall perceptions of the environment, and provide evidence that innovative lighting approaches and technologies are worth considering as an investment by hospital administrators looking to improve employees’ and patients’ perceptions of the patient room environment. This knowledge is intended to help facility designers and managers incorporate nurses’ perspectives in their decisions, as well as to inform technologists and engineers developing future generations of lighting systems for patient rooms. These future systems will utilize solid-state lighting technologies, such as LEDs, and will provide new opportunities for adapting the intensity, distribution, and spectrum of light to better satisfy the holistic needs of patients and caregivers at different times of day or night.

Davis, Robert G.↗

DOE OSTI2021

Composites of functional polymers: Toward physical intelligence using flexible and soft materials

Abstract Materials that can assist with perception and responsivity of an engineered machine are said to promote physical intelligence. Physical intelligence may be important for flexible and soft materials that will be used in applications like soft robotics, wearable computers, and healthcare. These applications require stimuli responsivity, sensing, and actuation that allow a machine to perceive and react to its environment. The development of materials that exhibit some form of physical intelligence has relied on functional polymers and composites that contain these polymers. This review will focus on composites of functional polymers that display physical intelligence by assisting with perception, responsivity, or by off-loading computation. Composites of liquid crystal elastomers, shape-memory polymers, hydrogels, self-healing materials, and transient materials and their functionalities are examined with a viewpoint that considers physical intelligence. Graphic Abstract

36 MATERIALS SCIENCE↗

DOE OSTI2020

On the Robustness of Network Community Structure Under Addition of Edges

Communities represent important functional modules in networked systems. A key goal in preserving such communities is understanding their robustness under perturbations. Previous research has studied the impact of node removals and edge removals on the community structure. However, the impact of edge additions on the robustness of the community structure is relatively unknown. Edge additions or false positive edges may simulate measurement errors or external exceptional events that threaten the functionality of networked systems. Here, we study the impact of edge additions on the community structure using Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks. We show that, for a fixed network size, the impact of edge additions is greater on networks with initially weak community structure than on networks with strongly clustered structures. In addition, we find that the perception of the impact is also dependent on the community detection algorithm used to uncover communities. In particular, we found that modularity-based methods such as Leiden and Louvain are less affected than information-theoretic and message passing-based methods such as Infomap and Label Propagation. Our results demonstrate that edge addition can (a) significantly impact the community structure of networks based on their initial conditions, and (b) the perception of the impact is dependent on the community detection algorithm used. We describe limitations, open challenges, and how this methodology can inform the design of resilient networked systems under edge additions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Development of Lighting Application Efficacy Measurement Framework

Lighting significantly contributes to electricity consumption in buildings. The most widely used measure of lighting energy efficiency, luminous efficacy, quantifies only the intensity of light generated by light sources, weighted by the spectral sensitivity of the human visual system (i.e., the energy efficiency of individual lighting devices). However, luminous efficacy does not fully address the use of lighting in architectural spaces. To address these limitations, we developed a framework to framework to calculate lighting application efficacy (LAE), the relationship between the electrical power consumed by lighting hardware, and the amount of light that contributes to the visual perception of building occupants. The proposed LAE framework is based on the primary pathway of light in architectural settings: the generation and emission of light from a luminaire, the travel of the light throughout the space and into the eyes of occupants, and the process of visual perception. The project’s primary outputs are a method for measuring lighting application efficacy and a framework for facilitating future research to improve the metric.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

A Framework for Streamlining Large Load Interconnection: An Assessment of Current Practices and Emerging Strategies for Fair and Efficient Load Interconnection Processes

This report focuses on current perceptions, challenges, and processes related to interconnection of LELs to the grid; while these loads include several types of entities, the primary focus of this work is on data centers, the largest current driver of this growth. It begins by summarizing relevant context related to load growth in the United States, including key stakeholder perceptions as data center deployment drive historic load growth nationwide. It then reviews the current landscape of large load interconnection processes and challenges and then proposes a framework of potential strategies intended to support a more consistent, streamlined, and fair approach to load interconnection. This framework is adapted from solutions proposed or adopted to address similar challenges faced in generator interconnection queues as well as notable reforms currently being proposed or enacted for large loads that could be more widely adopted.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Lighting application efficacy: A framework for holistically measuring lighting use in buildings

Lighting consumes significant energy in buildings, but current measurements of lighting efficiency are inadequate in capturing the spatial and temporal effectiveness of light. The most widely used lighting energy efficiency measure, luminous efficacy, quantifies the amount of light generated by individual light sources. While luminous efficacy provides manufacturers and designers with a useful metric for quantifying the energy efficiency of individual lighting devices, it does not fully address the use of lighting in architectural spaces. Instead, application efficacy, the relationship between the electrical power consumed by lighting hardware and the amount of light that contributes to the visual perception of building occupants, must be measured. Here, we propose a framework for calculating lighting application efficacy (LAE) based on the primary pathway of light in architectural settings: the generation and emission of light from a luminaire, the travel of the light throughout the space and into occupants’ eyes, and the process of visual perception. The LAE framework will include the development of computational methods for estimating the proportion of emitted light that is directed to task areas and areas corresponding to occupants’ visual fields using ray-tracing lighting design software. Future modeling and validation work will quantify energy efficiency of buildings.

Durmus, Dorukalp↗

DOE OSTI2021

Human-automated vehicle interactions

This dissertation is proposed to answer the question: how can the interactions between human and automated vehicles be used to improve the overall performance of automated driving technology? Multiple different modules in automated vehicles such as the perception, motion plan and motion control modules can potentially be benefitted from human-automated vehicle interactions. For perception module, the self-correction of faulty sensors can be achieved using human demonstration data. For motion plan and motion control modules, the performance of the low-level motion controller can be improved with the help of human demonstration, and the behavior of the motion planner can be improved using human intervention data during automated driving. Moreover, a better model for a human driver could improve the overall efficiency and comfort of vehicles in connected mixed traffic. In this dissertation, the technical research toward these goals has been completed and has resulted in several peer-reviewed publications. Optimization methods and model predictive control are used extensively to improve energy efficiency while maintaining safe and comfort driving. An inverse model predictive control (IMPC) method has been developed and it has been proven to be effective in modeling the motion of human driven vehicles. The proposed method has demonstrated its benefits in both connected automated highway driving and the bilateral adaptation of human driver and automated driving controller in human-in-the loop simulations. The proposed future research seeks to broaden the application of IMPC by considering a more comprehensive cost function design and applying it to more complex driving situations.

Guo, Longxiang↗

DOE OSTI2021

HUMAN-AUTOMATED VEHICLE INTERACTIONS

Guo, Longxiang↗

DOE OSTI2022

Contentious narratives and disinformation about nuclear weapons in strategic deterrence and competition: A SOCOM perspective. Part of Section: United States Special Operations Command (USSOCOM) in Emerging Strategic & Geopolitical Challenges: Operational Implications for US Combatant Commands

Russia’s “special military operation” in Ukraine demonstrates the challenge for strategic deterrence and competition of countering contentious narratives and disinformation about weapons of mass destruction (WMD) during conventional regional wars against a nucleararmed adversary. Moscow uses both tailored, contentious narratives and targeted disinformation about WMD in Ukraine to influence and disrupt local and global perceptions in support of its deterrence and competition objectives vis-à-vis the United States and NATO. Since December 2021, Moscow has made a focal point of chemical, biological, radiological, and nuclear weapons in its efforts to establish a permissive environment for its military buildup on the border with Ukraine and then its military intervention. These information tactics also demonstrate an opportunity for US Special Operations Forces (SOF). They are a case study for considering how SOF can contribute to strategic deterrence and competition objectives, specifically countering adversary gray-zone information efforts to alter regional security orders.1 Such a role is in line with the 2022 Special Operations Forces Vision and Strategy, which provides a framework for the evolution of SOF into “a force capable of creating strategic, asymmetric advantages for the nation as a key contributor of integrated deterrence” (United States Special Operations Command, 2022). This paper briefly examines this strategic challenge and SOF opportunity, focusing narrowly on the distinction between contentious narratives and disinformation about nuclear weapons and the role of SOF in countering these gray-zone information tactics. The nuclear dimension of Moscow’s contentious narratives and disinformation in the “special military operation” is of particular interest because it demonstrates the distinction between strategic efforts to influence and disrupt local and global perceptions in Moscow’s favor. This distinction between influence and disruption is less clear with Russia’s contentious narratives and disinformation about chemical and biological weapons in Ukraine, as disinformation about these two types of WMD appears to overwhelm contentious narratives. We believe this distinction is useful for policymakers and warfighters responsible for countering gray-zone information tactics because it provides a framework for crafting tailored responses to contentious narratives and disinformation about nuclear weapons and other WMD. The chapter concludes with a discussion of efforts that could be undertaken by SOF in cooperation with other relevant stakeholders to address this aspect of adversary gray-zone information tactics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Blending Behavioral Science and Physics-Based Models Inform Equitable Decarbonization Pathways in the US Housing Stock: Preprint

A just energy transition is an imperative of the Biden-Harris Administration, emphasizing the equitable distribution of benefits through energy-efficient and decarbonizing household technologies. Understanding the factors that increase a household's willingness to adopt these technologies helps policymakers implement more targeted and effective approaches. Our research addresses this by blending 550,000 housing stock types and energy simulation data with a nationally representative survey on residential technology adoption and decision-making (n=10,000). We identify energy equity gaps across tenure and income, highlighting disparities in energy burdens and insecurity. Findings show that households with prior modification experience are more willing to renovate, suggesting that small-scale retrofit programs could foster greater willingness. Energy secure but burdened homeowners are least willing to modify, highlighting the need to consider energy bill perceptions in policy design. Nearly half of US households that are energy burdened also face energy insecurity, with a significant gap in assistance for low-income households. We emphasize the need to understand household perceptions to improve policy. This research underscores the importance of understanding household behaviors to improve policy effectiveness, offering actionable insights for policymakers to promote equitable housing upgrades and advance a decarbonized future.

behavioral science↗

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↗

DOE OSTI2022

Convincing Clients to Make Zero a Reality: Preprint

As buildings are the largest end-users of carbon-intensive energy in the United States, it is critical that design and construction professionals implement energy-efficient and sustainable building designs and systems. Building owners seeking building energy performance improvements, either with new construction or retrofit of existing facilities, usually need the expertise of design and construction professionals to guide them through the process. These "trusted advisers" make the design decisions that ultimately result in the energy performance of the building. Members of the design and construction community have identified that clients' perception of cost associated with such designs and building upgrades have posed the most significant barrier to increased adoption. If solved, this would enable design and construction firms to better engage as trusted advisors along the lines of energy and carbon reduction of the built environment. NREL has developed a resource that helps design and construction professionals and their clients match their projects with financial incentives. A newly developed cohort of design and construction professionals, as part of the U.S. Department of Energy's Better Buildings Initiative, has brought real-world project experiences to the development process, contributing meaningful insights that have been critical to evaluating the successes of and providing direction to this much needed financial guide.

Better Buildings↗