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At least 1,171 records · Page 65

The water use of data center workloads: A review and assessment of key determinants

The global importance of data center water use is increasing with the rapid growth of digitalization and artificial intelligence. This study analyzes the factors influencing workload-level water use, measured in liters consumed per workload, to guide water-saving strategies in data centers. Our findings reveal workload-level water use variations exceeding 10,000-fold, driven by over 1000-fold differences in water consumption per kilowatt hour of server electricity consumed and approximately 10-fold differences in server workload efficiency. Key determinants are ranked as server efficiency, electrical grid water consumption factors, server utilization, cooling system type, infrastructure efficiency, climate zone, inactive server percentage, and server refresh cycle. Notably, there is no single recipe for minimizing water use; instead, optimal outcomes depend on tailored combinations of these factors. This analysis addresses critical knowledge gaps by identifying the determinants of data center water use and exploring their achievable minima under diverse site-specific constraints.

Data centers↗

Surface Profile and Stress Field Evaluation using Digital Gradient Sensing Method

Shape and surface topography evaluation from measured orthogonal slope/gradient data is of considerable engineering significance since many full-field optical sensors and interferometers readily output accurate data of that kind. This has applications ranging from metrology of optical and electronic elements (lenses, silicon wafers, thin film coatings), surface profile estimation, wave front and shape reconstruction, to name a few. In this context, a new methodology for surface profile and stress field determination based on a recently introduced non-contact, full-field optical method called digital gradient sensing (DGS) capable of measuring small angular deflections of light rays coupled with a robust finite-difference-based least-squares integration (HFLI) scheme in the Southwell configuration is advanced here. The method is demonstrated by evaluating (a) surface profiles of mechanically warped silicon wafers and (b) stress gradients near growing cracks in planar phase objects.

42 ENGINEERING↗

WE-G-204-08: Optimized Digital Radiographic Technique for Lost Surgical Devices/Needle Identification

Purpose: Small surgical devices and needles are used in many surgical procedures. Conventionally, an x-ray film is taken to identify missing devices/needles if post procedure count is incorrect. There is no data to indicate smallest surgical devices/needles that can be identified with digital radiography (DR), and its optimized acquisition technique. Methods: In this study, the DR equipment used is a Canon RadPro mobile with CXDI-70c wireless DR plate, and the same DR plate on a fixed Siemens Multix unit. Small surgical devices and needles tested include Rubber Shod, Bulldog, Fogarty Hydrogrip, and needles with sizes 3-0 C-T1 through 8-0 BV175-6. They are imaged with PMMA block phantoms with thickness of 2–8 inch, and an abdomen phantom. Various DR techniques are used. Images are reviewed on the portable x-ray acquisition display, a clinical workstation, and a diagnostic workstation. Results: all small surgical devices and needles are visible in portable DR images with 2–8 inch of PMMA. However, when they are imaged with the abdomen phantom plus 2 inch of PMMA, needles smaller than 9.3 mm length can not be visualized at the optimized technique of 81 kV and 16 mAs. There is no significant difference in visualization with various techniques, or between mobile and fixed radiography unit. However, there is noticeable difference in visualizing the smallest needle on a diagnostic reading workstation compared to the acquisition display on a portable x-ray unit. Conclusion: DR images should be reviewed on a diagnostic reading workstation. Using optimized DR techniques, the smallest needle that can be identified on all phantom studies is 9.3 mm. Sample DR images of various small surgical devices/needles available on diagnostic workstation for comparison may improve their identification. Further in vivo study is needed to confirm the optimized digital radiography technique for identification of lost small surgical devices and needles.

60 APPLIED LIFE SCIENCES↗

FAIR AI models in high energy physics

Abstract The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning models—algorithms that have been trained on data without being explicitly programmed—and more generally, artificial intelligence (AI) models, are an important target for this because of the ever-increasing pace with which AI is transforming scientific domains, such as experimental high energy physics (HEP). In this paper, we propose a practical definition of FAIR principles for AI models in HEP and describe a template for the application of these principles. We demonstrate the template’s use with an example AI model applied to HEP, in which a graph neural network is used to identify Higgs bosons decaying to two bottom quarks. We report on the robustness of this FAIR AI model, its portability across hardware architectures and software frameworks, and its interpretability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spatially Adaptive Tunable Lighting Control System with Expanded Wellness and Energy Saving Benefits

Lighting design is becoming increasingly complex, including active dimming for energy savings and spectral tuning for human wellbeing. Modern commercial lighting control systems are already difficult to use, and maintain, and even with so-called Smart Lighting, optimizing light settings is rapidly exceeding the capabilities of direct human control, limiting the adoption of lighting control systems. The growing importance of Occupancy Centric Controls (OCC) for advanced building management systems can be applied to the development of autonomous lighting system controls needed to drive the adoption of advanced lighting controls for improved adaptive “sculpted illumination” for both greater energy savings and broader human wellbeing perspectives. This project, led by Rensselaer Polytechnic Institute, entitled “Spatially adaptive tunable lighting control system with expanded wellness and energy saving benefits” will develop and test an entirely new platform for automated optimized lighting design and control that requires little or no human engagement, yet contours lighting profiles automatically to minimize lighting energy use. We call this approach to lighting control “dynamic light sculpting” since the right amount of illumination is automatically delivered to occupants in real time. Since the system uses new, privacy-preserving occupant position and pose detection technologies developed by Rensselaer for broad OCC building applications, the control system will analyze how to deliver the right amount of the right type of illumination only where and when it is needed based these OCC platforms. To create these powerful autonomous lighting control platforms, the project will integrate evolving augmented reality (AR) and virtual reality (VR) tools with sophisticated lighting and interior design toolkits to create interactive lighting design and control simulators. Using the quickly growing paradigm of digital twins, these tools will integrate light fixture properties, occupancy sensor data, interior design data, and lighting specifications to accurately visualize how various design concepts interact with simulated yet realistic human activities that occur in commercial office buildings of various types. These advanced digital twin design and simulation tools will be combined with a new class of digitally-programmable LED lighting fixtures that can dynamically change the spectral content and direction of light emission. When fully integrated, the new autonomous lighting control system will take all of the guesswork out of optimizing light quality while minimizing energy consumption. Digital twin tools will simplify the design, installation, commissioning, operation, and maintenance of future energy-efficient lighting systems. It should be possible to reduce lighting energy costs from 40% to 70% with OCC based dynamic light sculpting systems. The work will be led by the Center for Lighting Enabled Systems and Applications (LESA) and the Center for Architectural Science and Ecology (CASE), both at Renssealer Polytechnic Institute; Lumileds, a global leader in the development of advanced LED systems; and HKS, a leading global architecture design firm. This interdisciplinary project team’s experience includes all of the design simulation tools, VR/AR digital twin visualization technology, advanced occupancy sensing technology, and complex control system design capabilities that will revolutionize lighting design and control technology to autonomously deliver high-quality lighting that improves human health and wellbeing while simultaneously maximizing lighting energy savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Machine Learning Digital Twin for Lithium Ion Battery State of Health Predictions

A digital twin system has been established to model the long term degradation of the state of health of lithium ion batteries. Two data streams result from the computational model of the system and from the physical experiment measurements. A machine learning pipeline has been developed at the nexus of these data streams. Leveraging the unique data sources in multiple transfer learning approaches has lead to the development of multiple cell specific machine learning digital twins. Our discussion on this first of its kind technology will cover challenges in data ingestion, scalability, architecture and orchestration, and research findings.

25 - ENERGY STORAGE↗

Digitalization Guiding Principles and Method for Nuclear Industry Work Processes

The commercial U.S. light-water reactor fleet has been operating at historical efficiency, reliability, and safety over the last decade. Nuclear power has the highest capacity factor of any other power generation technology while also serving as the largest baseload source for carbon-free energy. Despite this remarkable achievement, continued operations for many plants are threatened due to fierce electricity market competition and rising operations and maintenance costs of which continued maintenance of obsolete analog equipment is a contributor. The digital age and associated technologies are where the future lies in process control, and nuclear has yet to take full advantage of the capabilities offered therein. The Light Water Reactor Sustainability Program (LWRS) at Idaho National Laboratory (INL), sponsored by the Department of Energy, has a mission to help the light-water reactor fleet manage its foundational capabilities to continue providing safe and reliable carbon-free power. LWRS helps support that mission by providing scientific, technology-based solutions for advanced concepts of operations with a more viable business model that will allow the fleet to continue to operate at peak levels through extended plant operation. The LWRS Digitalization Project at INL seeks to leverage digital technologies to synthesize and transform work processes. We provide a state-of-the-art analysis of digitalized work processes in nuclear power and investigate ways in which researchers at INL and the nuclear industry can work together to identify what data to access, how to access it, what to do with the data, and most importantly, how to use the insights for decision-making across all levels within the business. Borne from these considerations, we present four guiding principles for digitalization: develop a coherent digitalization plan, apply human factors engineering, establish data governance, and anticipate unintended consequences. Together, these principles form a method that plants can use to effectively to digitalize nuclear industry work processes. Our guiding principles are informed by multiple knowledge sources. First, we document activities from the Work Digitalization Initiative, which was conceived as a means for nuclear organizations to help define and standardize the industry’s approach to digitalizing work. Second, we detail primary research conducted with industry professionals regarding drivers and barriers to digitalization adoption. We present survey results that demonstrate what the industry hopes to get out of digitalization and the ways that INL can continue to support the industry’s digital transformation. Third, we present a digitalization use case with industry partners NextAxiom Technology and Xcel Energy. The project objective was to transform the current condition report work process from paper to digital, incorporating digitalized principles. We report the development of the application and lessons learned. The accomplishments achieved by this research and development serve to identify critical needs for plant guidance in support of digitalization implementation and contribute to the knowledge and strategies available for utilities considering or undertaking digitalization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Construction of occipital bone fracture using B-spline curves

Treating trauma to the cranio-maxillofacial region is a great challenge and requires expert clinical skills and sophisticated radiological imaging. The aim of reconstruction of the facial fractures is to rehabilitate the patient both functionally and aesthetically. In this article we employed B-spline curves to construct the occipital bone fracture using Digital Imaging and Communications in Medicine (DICOM) format data. The construction of occipital bone fracture starts with the boundary extraction followed by corner detection, construction of fractured part inner outer curve for each DICOM data using B-spline curves and finally the construction of fractured part in DICOM format. Method used in this article is based on DICOM data only and does not require any technique such as mirror imaging, technical help, reference skull, or to take average thickness of skull bone. Using the proposed method, the constructed fractured implant is custom made for every individual patient. At the end of this article we present a real case, in which we have constructed the occipital bone fracture using B-spline. The proposed method has been validated using post-operation DICOM data. For practical application, Graphical User Interface (GUI) has been developed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Development and data path integration test of the global Feature EXtractor for the ATLAS Level-1 calorimeter trigger system Phase-I upgrade

The global Feature Extractor (gFEX) is a component of the Phase-I upgrade of the Level-1 Calorimeter (L1Calo) trigger system for the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. The gFEX is used to identify patterns of energy associated with the hadronic decays of high momentum Higgs, W and Z bosons, top quarks, and exotic particles in real time at the 40 MHz LHC bunch crossing rate. Three prototypes were implemented and tested from 2014 to 2017. With the lessons learned from the prototypes, the final gFEX production board has been implemented at the end of 2017. The gFEX receives up to 300 fiber optical links from the calorimeter and transmits trigger data on 96 links to the ATLAS Level-1 Topological [1] (L1Topo) trigger at a rate of up to 12.8 Gb/s. There are also 24 electrical links on board for communication between two FPGAs running at speeds of up to 25.6 Gb/s. Here, the hardware functionality and performance of the production board have been evaluated. A data path integration test between the Liquid Argon Digital Processing Blade (LDPB) [2] and the Front End LInk eXchange (FELIX) [3] was performed successfully at CERN in 2018.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

BoxScore - A real-time beam-diagnosis program for the CAEN digitizer x730 series

BoxScore is a real-time beam diagnosis and monitoring program for the CAEN x730 series digitizer, developed for the ATLAS in-flight system at Argonne National Laboratory. The CAEN x730 series digitizer, with built-in Digital Pulse Processing for the Pulse-Height-Analysis, digitizes the input signal in real-time and processes it using a trapezoidal filter. BoxScore reads the digitizer’s buffer directly, builds and saves events to local files, plots histograms for particle identification, and outputs the rates of selected isotopes every second. Implementation of BoxScore has shortened the time needed for in-flight beam-tuning and has potential applications for other nuclear physics experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

X-ray and γ-ray beam interstellar communication and implications for SETI

The possibility of detecting artificial signals transmitted by alien civilizations via collimated X-ray or gamma-ray beams is investigated. The prospect of using such beams for human communication within the solar system and beyond is also discussed. Detector responses were simulated for input signals and analyzed using relative entropy. For simplicity, all signals were assumed to use on-off keying (OOK) modulation. “Real” signals were generated by taking digital files and sequentially feeding their raw binary data to the detector simulator, the resulting normalized information content of the detector signals was plotted and compared to random noise signals. Since jpeg files contain compressed information, these served as a proxy for artificial alien signals. This showed that there is a clear difference in measured information content between natural and artificial signals, even with relatively poor time resolution in the detector causing the signals to be smeared (dead-time/rise-time intervals many times longer than the duration between signal pulses). It was found that so long as the signal lasts for at least several rise-time/dead-time intervals, the distinction between random and artificial signals is obvious. A space-telescope with high time resolution for searching for such signals is briefly described and its basic requirements are outlined.

43 PARTICLE ACCELERATORS↗

Measurement of the rate of stellar tidal disruption flares

We report an observational estimate of the rate of stellar tidal disruption flares (TDFs) in inactive galaxies based on a successful search for these events among transients in galaxies using archival Sloan Digital Sky Survey (SDSS) multi-epoch imaging data (Stripe 82). This search yielded 186 nuclear flares in galaxies, 2 of which are excellent TDF candidates. Because of the systematic nature of the search, the very large number of galaxies, the long time of observation, and the fact that non-TDFs were excluded without resorting to assumptions about TDF characteristics, this study provides an unparalleled opportunity to measure the TDF rate. To compute the rate of optical stellar tidal disruption events, we simulate our entire pipeline to obtain the efficiency of detection. The rate depends on the light curves of TDFs, which are presently still poorly constrained. Using only the observed part of the SDSS light curves gives a model-independent upper limit to the optical TDF rate, N-dot <2×10{sup −4} yr{sup −1} galaxy{sup −1} (90% CL), under the assumption that the SDSS TDFs are representative examples. We develop three empirical models of the light curves based on the two SDSS light curves and two more recent and better-sampled Pan-STARRS TDF light curves, leading to our best estimate of the rate: N-dot {sub TDF}=(1.5--2.0){sub −1.3}{sup +2.7}×10{sup −5} yr{sup −1} galaxy{sup −1}. We explore the modeling uncertainties by considering two theoretically motivated light curve models, as well as two different relationships between black hole mass and galaxy luminosity, and two different treatments of the cutoff in the visibility of TDFs at large M {sub BH}. From this we conclude that these sources of uncertainty are not significantly larger than the statistical ones. Our results are applicable for galaxies hosting black holes with mass in the range of a few 10{sup 6}-10{sup 8} M {sub ☉}, and translates to a volumetric TDF rate of (4-8) × 10{sup –8±0.4} yr{sup –1} Mpc{sup –3}, with the statistical uncertainty in the exponent.

79 ASTRONOMY AND ASTROPHYSICS↗

Photometric variability in star-forming galaxies as evidence for low-mass AGN and a precursor to quenching

We measure the optical variability in ~16 500 low-redshift (z ~ 0.1) galaxies to map the relations between active galactic nucleus (AGN) activity and galaxy stellar mass, specific star formation rate, half-light radius, and bulge-to-total ratio. To do this, we use a reduced χ 2 variability measure on >10 epoch light curves from the Zwicky Transient Facility and combine with spectroscopic data and derive galaxy parameters from the Sloan Digital Sky Survey. We find that below the stellar mass of 10 11 M ⊙ , galaxies classed as star-forming via the Baldwin–Phillips–Terlevich diagram have higher mean variabilities than AGN or composite galaxies. Revealingly, the highest mean variabilities occur in star-forming galaxies in a narrow range of specific star formation rate: -11 < log(sSFR/yr -1 ) < -10. In very actively star-forming galaxies [log(sSFR/yr -1 ) > -10], the reduced variability implies a lack of instantaneous correlation with star formation rate. Our results may indicate that a high level of variability, and thus black hole growth, acts as a precursor for reduced star formation, bulge growth, and revealed AGN-like emission lines. These results add to the mounting evidence that optical variability can act as a viable tracer for low-mass AGNs and that such AGNs can strongly affect their host galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

The XMM Cluster Survey analysis of the SDSS DR8 redMaPPer catalogue: implications for scatter, selection bias, and isotropy in cluster scaling relations

ABSTRACT In this paper, we present the X-ray analysis of Sloan Digital Sky Survey DR8 redMaPPer (SDSSRM) clusters using data products from the XMM Cluster Survey (XCS). In total, 1189 SDSSRM clusters fall within the XMM–Newton footprint. This has yielded 456 confirmed detections accompanied by X-ray luminosity (LX) measurements. Of these clusters, 381 have an associated X-ray temperature measurement (TX). This represents one of the largest samples of coherently derived cluster TX values to date. Our analysis of the X-ray observable to richness scaling relations has demonstrated that scatter in the TX–λ relation is roughly a third of that in the LX–λ relation, and that the LX–λ scatter is intrinsic, i.e. will not be significantly reduced with larger sample sizes. Analysis of the scaling relation between LX and TX has shown that the fits are sensitive to the selection method of the sample, i.e. whether the sample is made up of clusters detected ‘serendipitously’ compared to those deliberately targeted by XMM. These differences are also seen in the LX–λ relation and, to a lesser extent, in the TX–λ relation. Exclusion of the emission from the cluster core does not make a significant impact on the findings. A combination of selection biases is a likely, but yet unproven, reason for these differences. Finally, we have also used our data to probe recent claims of anisotropy in the LX–TX relation across the sky. We find no evidence of anistropy, but stress this may be masked in our analysis by the incomplete declination coverage of the SDSS.

79 ASTRONOMY AND ASTROPHYSICS↗

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: tomographic BAO analysis of DR12 combined sample in Fourier space

In this work, we perform a tomographic baryon acoustic oscillations (BAO) analysis using the monopole, quadrupole and hexadecapole of the redshift-space galaxy power spectrum measured from the pre-reconstructed combined galaxy sample of the completed Sloan Digital Sky Survey Baryon Oscillation Spectroscopic Survey (BOSS) Data Release12 covering the redshift range of 0.20 < z < 0.75. By allowing for overlap between neighbouring redshift slices, we successfully obtained the isotropic and anisotropic BAO distance measurements within nine redshift slices to a precision of 1.5–3.4 percent for D V /r d , 1.8–4.2 percent for D A /r d and 3.7–7.5 percent for H r d , depending on effective redshifts. We provide our BAO measurement of D A /r d and H r d with the full covariance matrix, which can be used for cosmological implications. Our measurements are consistent with those presented in Alam et al., in which the BAO distances are measured at three effective redshifts. We constrain dark energy parameters using our measurements and find an improvement of the Figure-of-Merit of dark energy in general due to the temporal BAO information resolved. Finally, this paper is a part of a set that analyses the final galaxy clustering data set from BOSS.

79 ASTRONOMY AND ASTROPHYSICS↗

An 80-W 94.6%-Efficient Multi-Phase Multi-Inductor Hybrid Converter

This paper presents a new Multi-Phase Multi-Inductor Hybrid (MP-MIH) converter that features high efficiency at large conversion ratios, while operating the switches with duty cycles larger than state-of-the-art hybrid topologies. In this converter, the capacitors are soft-charged and soft-discharged through three inductors operated in three interleaving phases. An experimental six-level three-phase converter prototype achieves 94.6% peak efficiency and 425 W/in 3 power density for conversions from 48V to 1V-2V at loads of up to 40A. This multi-phase multi-inductor hybrid converter architecture can be extended to any number of switched-capacitor network levels to support wide range of input and output voltages and load currents in data centers, telecommunication and other high-performance digital systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Robust Predictive Control for Modular Solid-State Transformer With Reduced DC Link and Parameter Mismatch

This paper presents the analysis and implementation of a predictive control method for dc-link regulation and voltage balance in a cascaded modular reduced dc-link solid-state transformer (SST). Passive components like bulky dc links limit the power density of power converters, especially medium-voltage (MV) SST. Reduced dc-link or low-inertia converters can dramatically reduce the size, cost, and weight by tolerating larger dc-link ripples and improve the reliability with electrolytic capacitor-less dc link. However, a small dc link leads to tight coupling between the input and the output stages, which is a challenge for control design. In stacked low-inertia converters (SLIC), the low-inertia converter modules are stacked for MV applications, resulting in coupling between the modules and making the control more challenging. A new model predictive control method which can achieve deadbeat regulation on the dc link without weighting factors has been proposed to address this novel problem. This paper focuses on analyzing the condition of the low-inertia dc link up to 80% ripple, the robustness of the control under parameter mismatches, high-order terms, and important implementation issues such as model-based sampling and computation delay compensation. Significantly, the high-order terms are introduced because of the large dc-link ripple. These high-order terms are unique to the SLIC and negligible in conventional high-inertia converters. A discrete-time large-signal model is built to capture the dc-link’s nonlinear dynamics, and the eigenvalues of a small-signal Jacobian matrix are analyzed with Floquet theory to evaluate stability, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. Simulation and experimental results of an MVDC M-S4T verify the analysis and the predictive control method. Finally, the general application of the predictive control to low-inertia converters is compared against a conventional PI controller using a reduced dc-link active-front-end (AFE) rectifier as an example.

14 SOLAR ENERGY↗

Performance characterization of high quantum efficiency metal package photomultiplier tubes for time-of-flight and high-resolution PET applications

Purpose: Metal package photomultiplier tubes (PMTs) with a metal channel dynode structure have several advanced features for devising such time-of-flight (TOF) and high spatial resolution positron emission tomography (PET) detectors, thanks to their high packing density, large effective area ratio, fast time response, and position encoding capability. Here, we report on an investigation of new metal package PMTs with high quantum efficiency (QE) for high-resolution PET and TOF PET detector modules. Methods: The latest metal package PMT, the Hamamatsu R11265 series, is served with two kinds of photocathodes that have higher quantum efficiency than normal bialkali (typical QE ≈ 25%), super bialkali (SBA; QE ≈ 35%), and ultra bialkali (UBA; QE ≈ 43%). In this study, the authors evaluated the performance of the new PMTs with SBA and UBA photocathodes as a PET detector by coupling various crystal arrays. They also investigated the performance improvements of high QE, focusing in particular on a block detector coupled with a lutetium-based scintillator. A single 4 × 4 × 10 mm{sup 3} LYSO, a 7 × 7 array of 3 × 3 × 20 mm{sup 3} LGSO, a 9 × 9 array of 1.2 × 1.2 × 10 mm{sup 3} LYSO, and a 6 × 6 array of 1.5 × 1.5 × 7 mm{sup 3} LuYAP were used for evaluation. All coincidence data were acquired with a DRS4 based fast digitizer. Results: This new PMT shows promising crystal positioning accuracy, energy and time discrimination performance for TOF, and high-resolution PET applications. The authors also found that a metal channel PMT with SBA was enough for both TOF and high-resolution application, although UBA gave a minor improvement to time resolution. However, significant performance improvement was observed in relative low light output crystals (LuYAP) coupled with UBA. Conclusions: The results of this study will be of value as a useful reference to select PMTs for high-performance PET detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗