Novel Spin?Orbit Torque Generation at Room Temperature in an All-Oxide Epitaxial La[subscript 0.7]Sr
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Huang, Xiaoxi↗
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Results for “Generative Design”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Electrically Accelerated Mechanochemical Film Formation by a Phosphonium Phosphate Ionic Liquid: An In Situ Chemical Kinetics Investigation
Powertrains in electric vehicles are exposed to stray currents that accelerate wear and cause failure of mechanical components. These durability issues are further aggravated when using low-viscosity lubricants, which are desired for energy efficiency but create harsher contact conditions at sliding interfaces. This study investigates a phosphonium phosphate ionic liquid as a performance-enhancing additive in a low-viscosity base oil for lubricating electrified sliding interfaces. Ionic liquids can adsorb and react on contact interfaces via stress-assisted chemical reactions, generating nanometric tribofilms that provide protection against wear. However, the effect of electric fields on the mechanochemistry of ionic liquids is poorly understood, hindering their adoption in lubricants for electrified powertrains. This article reports an in situ optical interferometry study of ionic liquid derived tribofilm growth kinetics at stressed sliding/rolling interfaces under direct currents. The application of electric currents accelerated tribofilm formation up to a critical current density (∼1.4 A/mm 2 ), beyond which pitting-induced wear dominated. The tribofilms were composed of iron phosphates, iron oxides, and carbon species, with iron oxides becoming predominant under applied currents. These tribofilms prevented the scuffing failure of steel surfaces under electrified conditions. Based on the results, a kinetic model is proposed that integrates electric current effect into the classical stress-assisted thermal activation framework to allow prediction of tribofilm growth at electrified sliding contacts. This framework provides crucial guidance for designing next-generation lubricants for electrified transportation and power generation systems.
additives↗
Requirements and designs for Mars Rover RTGs
A typical Rover mission, its requirements, the environment it imposes on the radionuclide thermoelectric generator (RTG), and a design approach for making the RTG operable in such an environment are described. Specific RTG designs for various thermoelectric element alternatives are presented. The results of studies show that current multifoil-insulated GPHS (general-purpose heat source) RTG and Mod-RTG designs can be modified to operate in an environment with an external atmosphere (e.g., Mars). This can be done while the helium generated by the fuel's alpha decay is vented to the external atmosphere. The use of novel selective vents and high-capacity getters is not required. The Rover RTGs can be built from standard, proven GPHS modules and standard SiGe unicouples or SiGe/GaP multicouples, using demonstrated thermoelectric material performance parameters. Rover's 500-W power requirement can be satisfied with two 250-W or four 125-W RTGs, whose sizes are compatible with currently envisaged Rover designs. An auxiliary cooling loop (e.g., water and antifreeze) will be required to cool the RTG while it is within the Rover's aeroshell during launch and transit to Mars.
Schock, A.↗
Design of a Facility to Test the Advanced Stirling Radioisotope Generator Engineering Unit
The Advanced Stirling Radioisotope Generator (ASRG) is being considered to power deep space missions. An engineering unit, the ASRG-EU, was designed and fabricated by Lockheed Martin under contract to the Department of Energy. This unit is currently on an extended operation test at NASA Glenn Research Center to generate performance data and validate the life and reliability predictions for the generator and the Stirling convertors. A special test facility was designed and built for testing the ASRG-EU. Details of the test facility design are discussed. The facility can operate the convertors under AC bus control or with the ASRG-EU controller. It can regulate input thermal power in either a fixed temperature or fixed power mode. An enclosure circulates cooled air around the ASRG-EU to remove heat rejected from the ASRG-EU by convection. A custom monitoring and data acquisition system supports the test. Various safety features, which allow 2417 unattended operation, are discussed.
Lewandowski, Edward J.↗
A High-Pressure Shock Tube Study of Hydrogen and Ammonia Addition to Natural Gas for Reduced Carbon Emissions in Power Generation Gas Turbines
Ignition delay times from undiluted mixtures of natural gas (NG)/H2/Air and NG/NH3/Air were measured using a high-pressure shock tube at the University of Central Florida. The combustion temperatures were experimentally tested between 1000-1500 K near a constant pressure of 25 bar. Mixtures were kept undiluted to replicate the same chemistry pathways seen in gas turbine combustion chambers. Recorded combustion pressures exceeded 200 bar due to the large energy release, hence why these were performed at the high-pressure shock tube facility. The data is compared to the predictions of the NUIGMech 1.1 mechanism for chemical kinetic model validation and refinement. An exceptional agreement was shown for stoichiometric conditions in all cases but strayed at lean and rich equivalence ratios, especially in the lower temperature regime of H2 addition and all temperature ranges of the baseline NG mixture. Hydrogen addition also decreased ignition delay times by nearly 90%, while NH3 fuel addition made no noticeable difference in ignition delay time. NG/NH3 exhibited similar chemistry to pure NG under the same conditions, which is shown in a sensitivity analysis, demonstrating hydrogen chemistry to be dominant in NG/H2 mixtures and hydrocarbon chemistry to be dominant in NG/NH3 mixtures. The reaction CH3 + O2 = CH3O + O is identified and suggested as a possible modification target to improve model performance. Increasing the robustness of chemical kinetic models via experimental validation will directly aid in designing next-generation combustion chambers for use in gas turbines, which in turn will greatly lower global emissions and reduce greenhouse effects.
Pierro, Michael↗
Integrated Modeling for the Next Generation Space Telescope "Yardstick" Concept
The so-called NASA "Yardstick" design concept for the Next Generation Space Telescope presents unique challenges for systems-level analysis. Simulations that integrate controls, optics, thermal, and structural models are required to evaluate baseline performance, study design sensitivities, and perform design optimization. An integrated modeling approach was chosen using a combination of commercial off-the-shelf and "in-house" developed codes. The resulting capability provides a foundation for linear and non-linear analysis, using both the time and frequency-domain methods. It readily allows various combinations of design parameters and environmental loads to be evaluated directly in terms of key science-related metrics, in this case the scalar RMS (root mean square) line-of-sight and RMS wavefront errors. This presentation first addresses the development of the component, or discipline, models for the Yardstick design. It will then proceed to present the integration of the component models, using linear-systems approaches, in order to support two of the most critical baseline performance analyses: jitter and thermal-elastic stability of the optical telescope assembly (OTA). The results of the jitter analysis indicate that disturbances from the reaction wheels coupled with the lightly-damped and highly-flexible structure present significant challenges to the baseline line-of-sight control architecture. Vibration isolation will be required to meet jitter error requirements. The results of the thermal-elastic analysis indicate that the mirror segment displacements due to ground-to-orbit cool-down of the telescope are within the expected capture range of the segment rigid-body control actuators. This means we will be able to align and phase the primary mirror. However, the results for the analysis of the thermal transient response following an attitude maneuver (slew) show that this telescope design is not sufficiently stable, passively, to meet the wavefront error requirements. Structural re-design is one possibility; alternatively, active thermal control of the OTA may be considered. The Yardstick integrated models were successfully used to demonstrate the feasibility of two thermal control strategies.
Mosier, Gary E.↗
Understanding the Conductivity and Transference Trade-Off in Polymer Electrolytes Using a Robeson-Inspired Upper Bound
The development of high-performance electrolytes is crucial for advancing next-generation lithium and sodium battery technologies. Since the cation is the working ion in both technologies, electrolytes exhibiting the rapid cation transport are essential for making progress. Pathways to optimize electrolytes are unclear due to the inherent trade-off between conductivity and cation transference. While this trade-off is sometimes recognized, there are no well-accepted methodologies for quantifying it. Inspired by the Robeson upper bound for the permeability–selectivity trade-off in gas separation membranes, we propose an approach for quantifying the trade-off in electrolytes using Newman’s concentrated solution theory. We suggest calling this the Newman upper bound. By analyzing published data from 30 polymer electrolytes containing univalent lithium and sodium salts, the Newman upper bound is expressed as κ = 2.0(1/ρ+ – 1) where κ (mS/cm) is conductivity and ρ+ is the current fraction measured in a symmetric cell as first described by Bruce et al. [J. Electroanal. Chem. Interfacial Electrochem. 1987, 225 (1), 1–17]. This formulation of the upper bound introduces a critical guiding metric for designing next-generation polymer electrolytes; it highlights factors underlying the trade-off, including the salt diffusion coefficient (D), cation transference number relative to solvent velocity ( t + 0 ), and thermodynamic factor (1 + (d lnγ+–)/(d lnm)), where γ+– is the mean molar activity coefficient and m is the molality. These parameters have been measured for very few electrolytes. We posit that establishing the molecular properties that govern these parameters will lead to improved electrolytes that greatly exceed the current upper bound.
He, Zirong↗
Dual roles of stepped surfaces: Catalytic initiators and stabilizers of oxygen-induced reconstructions
Understanding surface restructuring under reactive conditions is crucial for designing next-generation catalysts with enhanced activity and selectivity. Here, we employ in situ transmission electron microscopy to directly observe the dynamic behavior of Cu(100) and Cu(410) surfaces under both oxidizing and vacuum annealing conditions, revealing a complex interplay among surface crystallography, local oxygen coverage, Cu atom mobility, and step-edge reactivity. The stepped Cu(410) surface acts as an active site for O 2 dissociation, triggering the oscillatory transformation of the c(2 × 2)–O phase into the more stable (2$\sqrt2$ ×$\sqrt2$)R45°–O missing-row (MR) structure on the adjacent flat Cu(100) terrace. Under subsequent vacuum annealing, this same Cu(410) facet exhibits remarkable structural resilience, preserving the MR reconstruction and chemisorbed oxygen. In contrast, the Cu(100) surface undergoes reversible transitions from the MR structure back to the c(2 × 2)–O phase. These results highlight the critical role of surface morphology in directing both the formation and stability of oxygen-induced reconstructions, demonstrating that stepped surfaces serve dual roles as both catalytic initiators and structural stabilizers. Furthermore, this work offers atomic-level insights into the environment-responsive behavior of copper surfaces, establishing a mechanistic basis for designing Cu-based catalysts through facet-specific control of surface reactivity.
36 MATERIALS SCIENCE↗
Spatiotemporal 4D Whole-cell Modeling of a Minimal Autotroph Reveals Central Carbon Metabolism Regulated Locally by Protein Megacomplexes via Post-translational Modifications under Light Disturbance
Photosynthetic microorganisms rely on multiple pathways in central carbon metabolism to adapt to fluctuating light and energy availability across diel cycles. Mechanistic insight into the regulatory dynamics of this adaptation requires integrating processes spanning disparate timescales, from rapid redox-dependent post-translational modifications (PTMs) to slower changes in protein expression and metabolic pathway usage. To address this complexity beyond genome-based inference and traditional modeling, we develop a whole-cell four-dimensional (3D + time) model of the marine cyanobacterium Prochlorococcus marinus MED4 that explicitly represents the spatial organization of enzymatic and molecular processes in central carbon metabolism under light perturbation. We employ a perturbation-based research design to experimentally generate time-series, multi-omics measurements that provide molecular descriptors and cryo-ET derived 3D segmented volumes as constraints for this dynamic 4D framework. The integration of experiments and modeling across defined light regimes enables quantitative validation of system-level responses and forecasting under distinct light disturbances. We test the hypothesis that light-dependent redox PTMs regulating the structural assembly of a protein megacomplex, the “dark complex,” modulate metabolic flux at a conserved regulatory node of the Calvin–Benson cycle (CBC) in cyanobacteria. Our model shows that subcellular spatial organization buffers rapid light-induced changes in thylakoid reaction rates, which are followed by redox-PTM-mediated sequestration or release of CBC enzymes in the dark complex, ultimately impacting carbon fixation dynamics within carboxysomes. Comparison with an equivalently parameterized well-mixed stochastic model demonstrates that post-translational regulation not only buffers transcriptional noise and diffusion-driven fluctuations but also stabilizes phenotypic outcomes, underscoring the importance of spatial heterogeneity in phenotypic robustness. This ability to probe adaptive, spatiotemporally resolved mechanisms in photosynthetic machinery and central carbon metabolism addresses a critical gap in genotype-to-phenotype inference and expands modeling and design capabilities for understudied or genetically intractable autotrophs such as P. marinus MED4.
Johnson, Connah G.↗
Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing
The geometric flexibility of additively manufactured metals and ceramics generates a very large and open design space that requires advanced modeling and simulation tools for physics simulations and the rigorous definition of design problems. This effort deploys artificial intelligence (AI) and machine learning (ML) algorithms to understand the design space, evaluate potential designs, and more efficiently generate optimized results. The Transformational Challenge Reactor (TCR) program is leveraging advances in several scientific areas—including materials, manufacturing, sensors and control systems, data analytics, and high-fidelity modeling and simulation—to accelerate the design, manufacturing, qualification, and deployment of advanced nuclear energy systems. Through a manufacturing-informed design approach, the TCR program seeks to integrate digital data for rapid nuclear innovation; accelerate the adoption of advances in manufacturing, materials, and computational sciences for nuclear applications; and dramatically reduce deployment costs and timelines for new nuclear reactor technologies. This report documents efforts under the TCR program to leverage advanced modeling and simulation techniques driven by AI/ML algorithms on high-performance computing (HPC) systems to yield more optimized TCR core designs. A multiphysics ML surrogate model was developed to run on the HPC architectures. The surrogate model is trained on high-fidelity simulation data of coupled neutronics and thermofluidics and is used to quickly evaluate thousands of candidate core designs in parallel, which drives the evolution of the cooling channel shapes to minimize temperature peaking and material stress. Outcomes from these activities provide design information and feedback into the core design efforts.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Modified Involute Helical Gears: Computerized Design, Simulation of Meshing and Stress Analysis
The computerized design, methods for generation, simulation of meshing, and enhanced stress analysis of modified involute helical gears is presented. The approaches proposed for modification of conventional involute helical gears are based on conjugation of double-crowned pinion with a conventional helical involute gear. Double-crowning of the pinion means deviation of cross-profile from an involute one and deviation in longitudinal direction from a helicoid surface. Using the method developed, the pinion-gear tooth surfaces are in point-contact, the bearing contact is localized and oriented longitudinally, and edge contact is avoided. Also, the influence of errors of alignment on the shift of bearing contact, vibration, and noise are reduced substantially. The theory developed is illustrated with numerical examples that confirm the advantages of the gear drives of the modified geometry in comparison with conventional helical involute gears.
COMPUTER AIDED DESIGN↗
Computational Modeling of Molten Salt Infiltration and Oxidation in Nuclear Graphite
Graphite is utilized as a moderator and reflector in advanced nuclear reactor designs due to its high thermal conductivity, neutron moderation properties, and resistance to radiation damage. However, its longterm performance and reliability are challenged by degradation mechanisms such as molten salt infiltration in molten salt reactors (MSRs) and oxidation in gas-cooled reactors (GCRs). These mechanisms can compromise the structural integrity and operational lifetime of graphite components, necessitating a more detailed assessment of their physical behavior. This report focuses on the development of computational models for molten salt infiltration and oxidation of graphite to aid the design and performance analysis of graphite components. For molten salt infiltration, a computational framework is developed that couples incompressible Navier-Stokes and phase-field model to simulate the penetration of molten salt into graphite?s interconnected pore structure. Initial model verification is performed using two-phase flows in two dimensions, demonstrating the models ability to capture fundamental physical behavior and agree with analytical solution. This framework is then applied to a realistic IG110 nuclear graphite , where a computed tomography extracted pore geometry is used to analyse the infiltration behavior of FLiNaK molten salt. This model provides insights into how the microstructure and other relevant parameters influence the transport pathways of molten salt into graphite, potentially offering a means to rapidly evaluate a graphite grade?s resistance to infiltration. For oxidation, the report details pore-scale mass and heat transport models, describing the diffusion of gases, reaction kinetics, and thermal effects. Additionally, this report highlights inconsistencies in the existing volume-averaged macroscopic model, particularly in upscaling of reaction kinetics and flux terms, and surface to volume transformations. These inconsistencies suggest that current formulations may not accurately capture the experimentally observed graphite oxidation process, highlighting the need for improved model development. This work advances the development of physics-based computational models for graphite degradation, contributing to improved predictive models for next-generation nuclear reactor designs. Future efforts will focus on refining the infiltration model to address non-physical behaviors and enhance its robustness. Additionally, for oxidation, further studies will employ the principles of volume averaging to rigorously derive the upscaled equations, potentially in collaboration with subject matter experts.
Computational Modeling of Molten Salt Infiltration↗
SODA: a New Synthesis Infrastructure for Agile Hardware Design of Machine Learning Accelerators
Next generation systems, such as edge devices, will have to provide efficient processing of machine learning (ML) algorithms along several metrics, including energy, performance, area, and latency. However, the quickly evolving field of ML makes it extremely difficult to generate accelerators able to support a wide variety of algorithms. At the same time, designing accelerators in hardware description languages (HDLs) by hand is hard and time consuming, and does not allow quick exploration of the design space. This paper discusses the SODA synthesizer, an automated open source high-level ML framework-to-Verilog compiler targeting ML Application-Specific Integrated Circuits (ASICs) chiplets based on the LLVM infrastructure. The SODA synthesizers will allow implementing optimal designs by combining templated and fully tunable IPs and macros, and fully custom components generated through high-level synthesis. All these components will be provided through an extendable resource library, characterized with both commercial and open source logic design flows. Through a closed loop design space exploration engine, developers will be able to quickly explore their hardware designs along different dimension
Minutoli, Marco↗
Incorporating Manual and Autonomous Code Generation
Code can be generated manually or using code-generated software tools, but how do you interpret the two? This article looks at a design methodology that combines object-oriented design with autonomic code generation for attitude control flight software. Recent improvements in space flight computers are allowing software engineers to spend more time engineering the applications software. The application developed was the attitude control flight software for an astronomical satellite called the Microwave Anisotropy Probe (MAP). The MAP flight system is being designed, developed, and integrated at NASA's Goddard Space Flight Center. The MAP controls engineers are using Integrated Systems Inc.'s MATRIXx for their controls analysis. In addition to providing a graphical analysis for an environment, MATRIXx includes an autonomic code generation facility called AutoCode. This article examines the forces that shaped the final design and describes three highlights of the design process: (1) Defining the manual to autonomic code interface; (2) Applying object-oriented design to the manual flight code; (3) Implementing the object-oriented design in C.
McComas, David↗
Understanding Interfacial Electrochemical Reactions through in situ ec-STEM and IL-Cryo-STEM
A major criterion in the design of next generation materials for electrical energy storage applications is a comprehensive understanding of interfacial electrochemical reactions as well as correlating the structure and chemistry across site-specific electrode/electrolyte interfaces with electron, charge, and mass transport processes as they govern performance characteristics. Scanning transmission electron microscopy (STEM) based techniques have emerged as an indispensable materials characterization tool that provides high spatial resolution imaging and chemical analysis and has been effectively utilized to obtain an atomic to nanoscale view of the interfacial structure before and after electrochemical cycling. More recently, there have been several advances that now allows us to obtain more detailed mechanistic insight into evolving reactions through in situ ec-STEM and electrical biasing platforms such as in the understanding of the mechanisms of solid electrolyte interphase formation, lithium dendrite nucleation and growth mechanisms and ionic transport mechanisms within intercalation, conversion, and alloying electrode materials. Several major advantages of the in situ ec-STEM approach is the quantitative electrochemical measurement of charge passed during cycling with simultaneous analysis of the electrochemical processes with STEM imaging and diffraction. Here, while spectroscopic analysis of the electrochemical reactions products has been performed, there is the issue of beam sensitivity and therefore, Cryo-STEM imaging combined with electron energy loss spectroscopy (EELS) techniques have been employed to analyze the chemistry of the SEI and Li dendrites. In this talk, we discuss the potential for combining identical location (IL) STEM techniques with Cryo-EM. The advantage of using this approach is that the sample is placed on a conventional TEM grid and the exact same location of the specimen can be analyzed before and after quantitative electrochemical measurements. Moreover, since the sample is on the TEM grid, the grid itself can be prepared for further Cryo-TEM experiments by plunge freezing in liquid nitrogen then transferred to the Cryo-TEM under liquid nitrogen. Results obtain from these experiments can be used to enhance our scientific understanding of interfacial chemistry at electrode/electrolyte interfaces and may be useful in the design of new materials.
36 MATERIALS SCIENCE↗
Design of a Preliminary Family of Airfoils for High Reynolds Number Wind Turbine Applications
For the past 30 years, offshore wind turbines exhibited a continual pattern of growth that is expected to continue as the industry pushes for higher efficiency. Current designs for the next generation of wind turbines are so large that the chordwise Reynolds number of the blades is well beyond the design range of existing open-source airfoil families. This paper presents a preliminary family of new airfoils designed specifically for the needs of these next-generation offshore turbines, ranging from 21% thick to 30% thick with operating Reynolds numbers between 12 million and 18 million. These airfoils are intended to be alternative to the FFA airfoils that are commonly used on reference turbines such as the IEA 15MW and 22MW designs. In this work, airfoil performance metrics and design targets are developed, the design process is outlined, an optimization scheme is presented, and finally the airfoils and their simulated performance are compared to existing baselines. Lift to drag ratios in a clean condition were improved by up to 49.3% from the baseline FFA airfoil, and rough condition lift to drag ratio was improved by up to 9.3%. It is estimated that the cumulative improvements provided by this airfoil family would result in an approximately 1% increase of Annual Expected Power (AEP) for the 22 MW turbine compared to the current baseline.
airfoils↗
New High-Entropy Perovskite Oxides with Increased Reducibility and Stability for Thermochemical Hydrogen Generation
This project aims to design, synthesize, and test a transformative class of High-Entropy Perovskite Oxides (HEPOs) as redox oxides to enable thermochemical hydrogen generation with improved stability, kinetics, and efficiency. These developed HEPOs are expected to demonstrate improved kinetics with oxygen surface exchange coefficient ( k > 7.5×10 -4 cm/s) in Budget Period (BP) 1, retain its structural stability in a broad range of oxygen non-stoichiometry (Δδ > 0.15) at a low operating reduction temperature of T red < 1400°C in BP 2, and deliver a H 2 yield of over 400 µmol per gram of oxide and high stability with less than 20% degradation after at least 50 cycles in BP 3. This project is feasible due to the unique thermodynamic properties (simultaneously increased reducibility and phase stability) and kinetic characters (stability against particle coarsening and potentially enhanced oxygen transport and surface reaction kinetics) of such HEPOs, and it is enabled by a unique active learning computational design approach. Computational studies have been conducted to investigate the oxygen vacancy formation in complex perovskite systems. * Accurate prediction of V O .. concentration with disordered A-site cations in Fe-based high-entropy perovskite oxides * Combined MC/DFT computation elucidates the mechanism of Co preference on the redox due to the strain introduced by local distortion. In this project, we explored a large number (~150) of perovskite compositions, which are listed in Tables 2 – 4). * All perovskite specimens have been synthesized through a high-throughput high-energy ball milling process, followed by the conventional sintering process. * XRD, SEM/EDS and TGA were performed to confirm the crystal structure, phase homogeneity and oxygen non-stoichiometry for compositionally complex perovskite oxides (CCPOs). * 110 compositions show single-phase from XRD * Unusual aliovalent doping effects in medium-entropy perovskite compositions. * V-shape relation between Δδ vs. x (La 1-x Sr x )(Mn 1/3 Fe 1/3 Ti 1/3 )O 3 * The highest reported hydrogen production for the CCPOs made in this project ( T re = 1350 ºC 30 min, T Ox = 1100 ºC 30 min) * B-site mixing (La 0.8 Sr 0.2 )(Mn 0.2 Fe 0.2 Co 0.4 Al 0.2 )O 3 : 89.97 ± 2.73 mmol H2 /mol oxide (395 ± 10 μmol/g oxide ) (i) No phase transformation during reactions when Co molar ratio is less than 61% (ii) Balance between intrinsic kinetics (oxygen surface exchange) and thermodynamics (oxygen non-stoichiometry) (iii) Preference of Co identified by in-situ XPS * A-site mixing (La 1/6 Pr 1/6 Nd 1/6 Gd 1/6 Ba 1/6 Sr1/6)MnO 3 : 98.48 mmol H2 /mol oxid e (~415 μmol/g oxide )
08 HYDROGEN↗
Residential electricity conservation in response to auto-generated, multi-featured, personalized eco-feedback designed for large scale applications with utilities
While past research has shown that providing residents with feedback about their electricity usage can reduce demand and its associated environmental burdens, some questions remain regarding what makes such feedback most effective. We followed the electricity usage of 36 residents who each received 14 feedback messages over 2 months. Using approaches borrowed from Natural-Language-Processing, feedbacks were generated automatically, using 10 features in random combinations. Unlike in previous studies, each resident received varying types of messages over time. In 504 observations, the average prompted reduction in electricity usage was 11 ± 3%, compared to a control group of 89 residents who received no messages. Feedback types prompting the largest reductions were self-comparisons with one’s own earlier usage (average reduction 14%) and messages of high variety from one feedback-cycle to the next (average reduction 16%). Comparisons with neighbors did not prompt higher reductions on average. Instead, they prompted reductions only when a resident’s recent usage happened to be higher than the average usage of neighbors, and increases when the reverse was true. Finally, this behavior was exhibited by all residents and is likely explained by a norm-conforming mean reversion of residents to their neighbors’ average usage, rather than an anti-conform “boomerang” behavior previously suggested in similar contexts.
42 ENGINEERING↗