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At least 397 records · Page 22

Field Test Report Neutron Scintillator Array Dry Storage Cask Scanner FY2024

During two weeks of Field Testing at the Idaho National Laboratory INTEC Cask Farm in July and August 2024, the LLNL Dry Storage Cask Scanner Array was lifted on top of an MC-10 dry storage fuel cask and operated to acquire neutron and gamma-ray data from the 24 fuel bundle positions. Neutron and gamma-ray data acquisition scans across the top of the cask of varying dwell times were performed July 15-18, 2024 and August 19-22, 2024 to evaluate the ability of the scanner data to reveal asymmetries in the fuel positions that reflect asymmetries in the MC-10 cask fuel bundle loading. The MC-10 cask 24 position fuel bundle loading at the INTEC Cask Farm is well documented, including the locations of six empty fuel bundle positions. This loading presents an opportunity to test the ability of the scanner system to detect diversion of spent fuel bundles as well as to validate the MC-10 cask MCNP modeling. The cask scanner array consists of six Stilbene crystal scintillator detectors and a linear actuator frame that moves the six detectors across the MC-10 dry storage cask to obtain data above each of the 24 fuel bundle positions. The detectors are connected to a pulse-shape discrimination data acquisition system capable of generating separate neutron and gamma-ray spectra for each detector and for each scan position. From the prior single detector Field Test in 2021 and iteration with MCNP modeling, the neutron and gamma-ray data were analyzed in multiple energy regions to identify an analysis method that would provide the strongest and most consistent signature of the asymmetric MC-10 cask fuel loading1 . From both the 2021 Field Test and the current Field Test results, the neutron capture gamma-ray count rate around 2.2 MeV provides the strongest signature of the asymmetric MC-10 cask fuel loading and has qualitative agreement with MCNP calculations. Counting all gamma-rays produces a similar signature. Neutrons emerging from the cask top are moderated and captured by the hydrogen in the polyethylene moderator and scintillator detector, producing a 2.2 MeV gamma ray which is seen in the scintillator gamma-ray spectrum. The count rate in the 2.2 MeV gamma-ray region is ~50 c/s, which is ~1000x higher than the ~0.05 n/s rate in the > 4MeV neutron region, and ~50x greater than the ~1 n/s rate in the neutrons > 500 keV region. Analysis of the 2.2 MeV neutron-capture Compton-scattered gamma-rays produces a statistically significant signature of the INTEC Cask Farm MC-10 asymmetric fuel loading. MCNP simulations indicate that the average neutron energy spectrum offers the potential to detect a large asymmetry from several missing bundles as well as individual missing fuel bundles. Testing this feature will require measurements on a cask with single missing elements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Street context of various demographic groups in their daily mobility

Abstract We present an urban science framework to characterize phone users’ exposure to different street context types based on network science, geographical information systems (GIS), daily individual trajectories, and street imagery. We consider street context as the inferred usage of the street, based on its buildings and construction, categorized in nine possible labels. The labels define whether the street is residential, commercial or downtown, throughway or not, and other special categories. We apply the analysis to the City of Boston, considering daily trajectories synthetically generated with a model based on call detail records (CDR) and images from Google Street View. Images are categorized both manually and using artificial intelligence (AI). We focus on the city’s four main racial/ethnic demographic groups (White, Black, Hispanic and Asian), aiming to characterize the differences in what these groups of people see during their daily activities. Based on daily trajectories, we reconstruct most common paths over the street network. We use street demand (number of times a street is included in a trajectory) to detect each group’s most relevant streets and regions. Based on their street demand, we measure the street context distribution for each group. The inclusion of images allows us to quantitatively measure the prevalence of each context and points to qualitative differences on where that context takes place. Other AI methodologies can further exploit these differences. This approach presents the building blocks to further studies that relate mobile devices’ dynamic records with the differences in urban exposure by demographic groups. The addition of AI-based image analysis to street demand can power up the capabilities of urban planning methodologies, compare multiple cities under a unified framework, and reduce the crudeness of GIS-only mobility analysis. Shortening the gap between big data-driven analysis and traditional human classification analysis can help build smarter and more equal cities while reducing the efforts necessary to study a city’s characteristics.

Salgado, Ariel (ORCID:0000000177015372)↗

Configurational stability of a crack propagating in a material with mode-dependent fracture energy – Part II: Drift of fracture facets in mixed-mode I+II+III

In earlier papers (Leblond et al., 2011; 2019), we presented linear stability analyses of the coplanar propagation of a crack loaded in mixed-mode I+III, based on a “double” propagation criterion combining (Griffith, 1920)’s energetic condition and (Goldstein and Salganik, 1974)’s principle of local symmetry. The difference between the two papers was that in the more recent one, the local value of the critical energy-release-rate was no longer considered as a constant, but heuristically allowed to depend upon the ratio of the local mode III to mode I stress intensity factors. This led to a much improved, qualitatively acceptable agreement of theory and experiments, for the “threshold” value of the ratio of the unperturbed mode III to mode I stress intensity factors, above which coplanar propagation becomes unstable. In this paper, the analysis is extended to the case where a small additional mode II loading component is present in the initially planar configuration of the crack, generating a small, general kink of this crack from the moment it is applied. The main new effect resulting from presence of such a loading component is that the instability modes present above the threshold must drift along the crack front during its propagation. This prediction may be useful for future theoretical interpretations of a number of experiments where such a drifting motion was indeed observed.

36 MATERIALS SCIENCE↗

Noninvasive Detection, Tracking, and Characterization of Aerogel Implants Using Diagnostic Ultrasound

Medical implants are routinely tracked and monitored using different techniques, such as MRI, X-ray, and ultrasound. Due to the need for ionizing radiation, the two former methods pose a significant risk to tissue. Ultrasound imaging, however, is non-invasive and presents no known risk to human tissue. Aerogels are an emerging material with great potential in biomedical implants. While qualitative observation of ultrasound images by experts can already provide a lot of information about the implants and the surrounding structures, this paper describes the development and study of two simple B-Mode image analysis techniques based on attenuation measurements and echogenicity comparisons, which can further enhance the study of the biological tissues and implants, especially of different types of biocompatible aerogels.

36 MATERIALS SCIENCE↗

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗

Multi-frame, ultrafast, x-ray microscope for imaging shockwave dynamics

Inertial confinement fusion (ICF) holds increasing promise as a potential source of abundant, clean energy, but has been impeded by defects such as micro-voids in the ablator layer of the fuel capsules. It is critical to understand how these micro-voids interact with the laser-driven shock waves that compress the fuel pellet. At the Matter in Extreme Conditions (MEC) instrument at the Linac Coherent Light Source (LCLS), we utilized an x-ray pulse train with ns separation, an x-ray microscope, and an ultrafast x-ray imaging (UXI) detector to image shock wave interactions with micro-voids. To minimize the high- and low-frequency variations of the captured images, we incorporated principal component analysis (PCA) and image alignment for flat-field correction. After applying these techniques we generated phase and attenuation maps from a 2D hydrodynamic radiation code (xRAGE), which were used to simulate XPCI images that we qualitatively compare with experimental images, providing a one-to-one comparison for benchmarking material performance. Moreover, we implement a transport-of-intensity (TIE) based method to obtain the average projected mass density (areal density) of our experimental images, yielding insight into how defect-bearing ablator materials alter microstructural feature evolution, material compression, and shock wave propagation on ICF-relevant time scales.

47 OTHER INSTRUMENTATION↗

Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system

Complex social-ecological systems can be difficult to study and manage. Simulation models can facilitate exploration of system behavior under novel conditions, and participatory modeling can involve stakeholders in developing appropriate management processes. Participatory modeling already typically involves qualitative structural validation of models with stakeholders, but with increased data and more sophisticated models, quantitative behavioral validation may be possible as well. In this study, we created a novel agent-basedmodel applied to a specific context: Zimbabwean non-governmental organization the Muonde Trust has been collecting data on their agro-pastoral system for the last 35 years and had concerns about land-use planning and the effectiveness of management interventions in the face of climate change. We collaboratively created an agent-based model of their system using their data archive, qualitatively calibrating it to the observed behavior of the real system without tuning any parameters to match specific quantitative outputs. We then behaviorally validated the model using quantitative community-based data and conducted a sensitivity analysis to determine the relative impact of underlying parameter assumptions, Indigenous management interventions, and different rainfall variation scenarios. We found that our process resulted in a model which was successfully structurally validated and sufficiently realistic to be useful for Muonde researchers as a discussion tool. The model was inconsistently behaviorally validated, however, with some model variables matching field data better than others. We observed increased model system instability due to increasing variability in underlying drivers (rainfall), and also due to management interventions that broke feedbacks between the components of the system. Interventions that smoothed year-to-year variation rather than exaggerating it tended to improve sustainability. The Muonde trust has used the model to successfully advocate to local leaders for changes in land-use planning policy that will increase the sustainability of their system.

54 ENVIRONMENTAL SCIENCES↗

Damage Accumulations Predictions for Boiler Components Via Microstructurally Informed Material Models

The goal of the project was to model material behavior and degradation during cyclic plasticity— with and without hold time—for nickel-based superalloys used in USC (ultra-super-critical) and A-USC (advanced-ultra-super-critical) boiler components. The study provided physically informed models, capturing the microstructural changes taking place in the industrial components under cyclic loading and long duration stress (up to 300,000 hours) and high temperature exposure (1100°F/593°C to 1400°F/760°C). The major developments were: 1) Qualitative and quantitative understanding of microstructure evolution (gamma prime precipitates), deformation (dislocation density), and damage mechanisms of Haynes ® 282 alloy. 2) Qualitative understanding of microstructural features generating local strain variations. 3) A continuum damage mechanics model (CDM) for Haynes ® 282 alloy at 1100°F to 1400°F capturing cyclic behavior with and without hold time. 4) Structural analysis for creep and LCF life predictions of an USC thick-wall Grade 91 superheater steel header and understanding life sensitivity to wall thickness of an AUSC Haynes ® 282 header.

20 FOSSIL-FUELED POWER PLANTS↗

Detection of Anatoxins in Human Urine by Liquid Chromatography Triple Quadrupole Mass Spectrometry and ELISA

Harmful cyanobacterial blooms are becoming more common and persistent around the world. When in bloom, various cyanobacterial strains can produce anatoxins in high concentrations, which, unlike other cyanobacterial toxins, may be present in clear water. Potential human and animal exposures to anatoxins occur mainly through unintentional ingestion of contaminated algal mats and water. To address this public health threat, we developed and validated an LC-MS/MS method to detect anatoxins in human urine to confirm exposures. Pooled urine was fortified with anatoxin-a and dihydroanatoxin at concentrations from 10.0 to 500 ng/mL to create calibrators and quality control samples. Samples were diluted with isotopically labeled anatoxin and solvent prior to LC-MS/MS analysis. This method can accurately quantitate anatoxin-a with inter- and intraday accuracies ranging from 98.5 to 103% and relative standard deviations < 15%, which is within analytical guidelines for mass spectrometry methods. Additionally, this method qualitatively detects a common degradation product of anatoxin, dihydroanatoxin, above 10 ng/mL. We also evaluated a commercial anatoxin-a ELISA kit for potential diagnostic use; however, numerous false positives were detected from unexposed individual human urine samples. In conclusion, we have developed a method to detect anatoxins precisely and accurately in urine samples, addressing a public health area of concern, which can be applied to future exposure events.

urine↗

A Spatially Explicit Individual-Based Modeling Approach to Evaluate the Cumulative Effects of Wind Energy Development on the Greater Sage-Grouse: Sensitivity Analysis and Validation of Key Parameters

To address the need for an approach to evaluate cumulative ecological impacts of wind energy development, particularly those on critical wildlife habitats and species, the authors developed a proof-of-concept, landscape-based, spatially explicit individual-based modeling (IBM) framework for populations of the greater sage-grouse (Centrocercus urophasianus) in Albany County, Wyoming, based on published and other available information on the life history of the species. This sage-grouse IBM estimates the spatial and temporal movements of sage-grouse based on modeled effects of habitat characteristics and developments on sage-grouse condition, survivorship, and reproduction. After completing the initial version of the model, we conducted a series of sensitivity analyses of key model parameters and validation of lek occurrences and spatial distributions to better understand performance of the model relative to observed values of important life history characteristics. The parameter sensitivity analysis was conducted as a series of one-factor-at-a-time tests in which the values of selected parameters were individually varied to evaluate the corresponding effects on model output. We examined the model’s response to changes in parameter values to gain insight into the overall robustness of the model, identify key driver parameters, and initiate qualitative validation. Five functions selected for sensitivity analyses were (1) the rate of change in body condition in relationship to habitat suitability index (HSI) of occupied habitat (condition change rate), (2) the effect of competition between individuals with overlapping home ranges expressed as a percentage reduction in HSI (competition factor), (3) value of condition at which survivorship probability is equal to zero (zero survivorship condition), (4) the relationship between female body condition and clutch size, and (5) the relationship between female body condition and nest success. We varied the parameter values to be tested for the sensitivity analysis around the original value used in the model (i.e., tested values were higher and lower than the model’s original value) to examine the effect of this variation on the predicted output of the model. Model outputs evaluated in the sensitivity analysis included (1) predicted age-class distribution (as measured by the percentage of immature individuals within the population); (2) predicted sex ratio; (3) predicted age-sex class distribution (percent of population in each of six age-sex classes, i.e., male and female juveniles, yearlings, and adults); (4) lifespan; (5) population size; and (6) spatial distribution. Of the five parameters analyzed, condition change rate, survivorship, clutch size, and nest success did not substantially affect any of the evaluated model outputs. For the predicted age-class distribution, the percentage of immature individuals predicted by the model for these four parameters ranged from 61.9% to 65.0%, which was reasonable with respect to the reference values of 51.4 to 57.8% in published studies. The ratio of females to males ranged from 1.09 to 1.14, which was comparable to the reference values of 1.2 to 3.0 presented in an existing study. The predicted mean lifespan ranged from 1.62 to 1.74 years, which appears to be reasonable with respect to the reference values of 0.9 to 1.1 years for sharp-tail grouse and greater prairie chickens presented by published studies. The predicted population size ranged from 1,877 to 3,140. This prediction would be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county. The predicted spatial distribution was not substantially affected by the parameter values examined. In our sensitivity analyses, the only tested parameter that had a noticeable effect on model output was competition factor. Over the range of values tested for this parameter, predicted population size exhibited the largest range (from 1,833 to 4,737) of all parameters tested. As the competition factor increased, the predicted population size decreased. This reflects the effect competition had on the number of individuals that could co occur in high-quality habitat patches. Despite this apparently significant effect, the range of values appears to be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county.

17 WIND ENERGY↗

Full circle mechanical dynamic characterization including experimental modal analysis and finite element analysis

During operation, it was observed that a specific mechanical system experienced undesirable vibration and it became necessary to understand and mitigate this phenomenon. This document investigates the tools, methodology, and results of the dynamic characterization of the system. The characterization makes use of the experimental modal analysis (EMA) methods of single input multiple output (SIMO) and single input single output (SISO). The validity of the theory of reciprocity is confirmed to minimize measurement error, cost, and time of repeat testing. Finite element analysis (FEA) is used in choosing transducer and modal impact locations to adequately characterize the system. Single degree of freedom (SDOF) and multiple degree of freedom (MDOF) curve fitting is used to fully characterize the system’s mode shapes and natural frequencies. The EMA characterization results are used to modify and validate the FEA model so that FEA can be used to model potential structural modifications to the system to mitigate the undesirable vibration. Structural modifications are chosen, implemented, and their effectiveness is quantified using EMA. Finally, a qualitative evaluation of the methodology of FEA validation by EMA and tuning of the model to match the experimental results is discussed.

42 ENGINEERING↗

Functional Relevance of CASP16 Nucleic Acid Predictions as Evaluated by Structure Providers

ABSTRACT Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non‐canonical regions where, for example, the nucleic‐acid backbone bends, deviating from an A‐form helix geometry, or a base forms a non‐standard hydrogen bond (not a Watson‐Crick base pair). These bends and non‐canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.

Biochemistry & Molecular Biology↗

Sulfonated Aromatic Polypentenamers: Scope of the Acetyl Sulfate Reaction

A precision polymer featuring one phenyl pendant at every fifth carbon on a polyethylene backbone was modified to varying degrees of sulfonation (DS = 33–98%) using acetyl sulfate with standard conditions by varying reaction times (up to 48 h). This soft, homogeneous method allows for evenly distributed phenylsulfonic acid groups with minimal side reactions and results in light brown, transparent materials with glass transition temperatures of 33–78 °C that increase with DS and parent polymer molar mass. The DS was accurately determined through well-resolved 1 H NMR (DSHNMR) signals of the regularly spaced phenyl groups and corroborated by inverse-gated decoupling 13 C NMR analysis. These analyses were compared to a series of other commonly accepted methods for DS determination including titration and elemental analysis (EA). The DS by titration (DS titr ) also increased with reaction time but was consistently lower than those determined by NMR. Significant discrepancies between theoretical and measured sulfur mass were observed for several samples through EA. Qualitative methods, such as infrared spectroscopy and thermal analyses, were also performed and correlated well with the DS determined by NMR. Here, this study presents a promising method to achieve a complete scope of homogeneous sulfonation from mild reaction conditions and presents a case to determine DS through multiple methods, with spectroscopic analyses, such as NMR, being potentially the most valuable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electron recombination of rotationally cold D 2 H + ions

Dissociative recombination (DR) of electrons with small molecular ions is a fundamental process for the physics and chemistry of the interstellar medium and planetary atmospheres. In previous DR studies, detailed analysis of the experimental rate coefficients has been hindered by the difficulty of preparing the ions in well-defined quantum states. For polyatomic ions in particular, truly state-selective measurements have been elusive, allowing only qualitative benchmarks of theory. Here, we present DR studies of the deuterated triatomic hydrogen ion D 2 H + , where the molecular ions were stored for up to 1000 seconds inside the Cryogenic Storage Ring (CSR) prior to the DR measurements. Our experiments with rotationally cold D 2 H + ions allow for detailed comparison to state-of-the-art theoretical calculations. We obtain very good agreement between experiment and theory even in the important collision energy range from 1 meV to 0.5 eV, where a multitude of Rydberg resonances reveal their imprint on the rate coefficient.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Binning is Sinning: Redemption for Hubble Diagram Using Photometrically Classified Type Ia Supernovae

Bayesian Estimation Applied to Multiple Species (BEAMS) is implemented in the BEAMS with Bias Corrections (BBC) framework to produce a redshift-binned Hubble diagram (HD) for Type Ia supernovae (SNe Ia). BBC corrects for selection effects and non–SN Ia contamination, and systematic uncertainties are described by a covariance matrix with dimension matching the number of BBC redshift bins. For spectroscopically confirmed SN Ia samples, a recent "Binning is Sinning" article showed that an unbinned HD and covariance matrix reduces the systematic uncertainty by a factor of ~1.5 compared to the binned approach. Here we extend their analysis to obtain an unbinned HD for a photometrically identified sample processed with BBC. To test this new method, we simulate and analyze 50 samples corresponding to the Dark Energy Survey (DES) with a low-redshift anchor; the simulation includes SNe Ia, and contaminants from core-collapse SNe and peculiar SNe Ia. The analysis includes systematic uncertainties for calibration and measures the dark energy equation of state parameter (w). Compared to a redshift-binned HD, the unbinned HD with nearly 2000 events results in a smaller systematic uncertainty, in qualitative agreement with BHS21, and averaging results among the 50 samples we find no evidence for a w-bias. To reduce computation time for fitting an unbinned HD with large samples, we propose an HD-rebinning method that defines the HD in bins of redshift, color, and stretch; the rebinned HD results in similar uncertainty as the unbinned case, and shows no evidence for a w-bias.

79 ASTRONOMY AND ASTROPHYSICS↗

Microstructural evolution in doped high entropy alloys NiCoFeCr-3X (X=Pd/Al/Cu) under irradiation

Commonly studied equatomic single-phase FCC high entropy alloys based on 3d transition metals like NiCoFeCr do not provide adequate strength and radiation resistance at high doses for nuclear structural applications. In the current study, the major alloying effects like lattice distortion, ordering and clustering tendencies were investigated by adding low concentration of Pd, Al, or Cu respectively to study the doping effects on the ion irradiation response of NiCoFeCr alloy. The alloys were irradiated with 3 MeV Ni 2+ ions at 500 °C to a fluence of 1 × 10 17 /cm 2 at a beam flux of approximately 2.8 × 10 12 ions/cm 2 /s. The microstructural evolution upon irradiation i.e., formation of dislocation networks, radiation induced segregation and precipitation, and void formation were studied in detail. Further, post-irradiation characterization results showed that a Pd addition leads to a high void nucleation rate but controlled void growth, which may be attributed to increased lattice distortion. In Al added HEA, our microstructural analysis indicates that radiation induced ordered L1 2 precipitates do not affect void swelling significantly. Cu addition led to Cu precipitation that drastically suppressed dislocation density and void swelling of the alloy. Additionally, a model was developed to qualitatively describe the trend in void swelling of typical FCC alloys under ion irradiation. This model was able to qualitatively explain the suppression and reappearance of void swelling in ion irradiated alloys that generally occurs near the region with peak implanted ion concentration.

36 MATERIALS SCIENCE↗

From Simple Labels to Time-Use Integrations: Supporting the Spectrum of Qualitative Travel Behavior Data

In transportation research, applications of travel behavior data collection are context-specific and require different types of qualitative inputs. These inputs can be viewed as spanning a spectrum of user burden and data quality, from simple trip labels to complex time-use surveys. However, each currently active smartphone-based travel diary platform appears to only support one type of qualitative input, and the effort required for customization is unclear. In this paper, we characterize the spectrum by defining four canonical use cases: (i) trip labels, (ii) trip questionnaire, (iii) counterfactual trips, and (iv) time-use surveys. We then outline a mechanism for supporting configurable user inputs on the same underlying smartphone-based sensing mechanism and demonstrate that it can support all the use cases without any code changes. We further demonstrate that the flexible data model that underpins this mechanism can enable real-time monitoring and analysis. Finally, we evaluate per-user data collection and engagement metrics for large-scale deployments of three canonical use cases, spanning 10 programs, 435 users, and 251,041 trips, and a maximum duration of 800 days. Future efforts may support additional use cases through an expanded configuration and provide greater insight into user engagement. We hope that these insights enable the research community to look at qualitative inputs through a new lens and experiment with novel use cases to fill in the spectrum.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

Lighting Control in Patient Rooms: Understanding Nurses’ Perceptions of Hospital Lighting Using Qualitative Methods

Here, this study differs in its methodological approach from previously published research by interpreting qualitative results against existing literature to understand how nurses conceptualize medical–surgical patient rooms as productive settings in relation to lighting, as well as the ways in which nurses believe these spaces could be enhanced for patient satisfaction. Content analysis was used to interpret themes emerging from nurses’ subjective responses to open-ended items. Three of the facilities had older, traditional lighting systems; one had a contemporary framework. A theme of environmental control over both overhead and task lighting emerged from data from all items. Although controllability was among the “best” lighting attributes, more refinement is necessary for optimal staff productivity and patient satisfaction. Daylighting was also considered to be among the best attributes. Control over light level via additional dimming capability for patients, as well as additional light sources, was prominent across the four hospitals. Unique to the more modern facility, trespassing of light was problematic for nurses considering the experiences of patients—even where modern models exist, more attention can be paid to the ways in which window shades, and light sources outside of rooms, penetrate spaces and affect users. Finally, the finding that nurses and patients desire greater control over the lighting in patient rooms is consistent with Ulrich’s theory of supportive design for healthcare and coincides with advances in lighting technology. Despite differences in the level of sophistication in lighting among the four facilities, control continues to be a primary concern for nurses.

60 APPLIED LIFE SCIENCES↗