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The California Statewide Travel Survey was conducted in 1991. Data were collected from 17,040 households throughout the state, with a minimum of 500 samples in any one region. The survey was primarily used to update trip generation rates.
What is the dollar value of increasing compliance with the energy code? Ultimately, this is the question that policy makers, funders, and program implementers care about. With this in mind, Pacific Northwest National Laboratory (PNNL) developed a new methodology capable of determining how much energy cost savings could potentially be gained through better compliance with the code (Rosenberg et al. 2016). On March 2, 2016 DOE issued Funding Opportunity Announcement (FOA) Number DE-FOA-0001532, requesting proposals to develop and test a methodology for identifying the commercial energy code requirements that can provide the maximum cost-effective energy and cost savings through increased compliance. Awarded to the Institute for Market Transformation, this report summarizes the development and testing of a commercial code compliance methodology, including a summary of results, statistical analysis of sample, and best practices for others implementing a commercial energy code compliance field study.
Due to their potential applications in low-power consumption and/or multistate memory devices, multiferroic materials have attracted a lot of attention in the condensed matter community. As part of the effort to identify new multiferroic compounds, perovskite-based GdCrO 3 was studied in both bulk and thin film samples. A strong enhancement of the capacitance in a field suggested ferroelectric behaviour but significant leakage and no well developed P–E hysteresis loops were observed. Measurements clearly indicate the existence of a polar phase but only below 2 K (likely connected to Gd ordering). Here the determination of the magnetic structure through neutron diffraction collected on an isotopic 160 GdCrO 3 sample at the WISH diffractometer at ISIS is reported. The presence of three successive magnetic phases as a function of temperature (commensurate, spin re-orientation and incommensurate phases once the Gd order), previously only seen by magnetization, is confirmed. Using the most recent guidelines for reporting the determined structures, we highlight the benefits of using such nomenclature for discussing physical properties and consider possible mechanisms and couplings that led this seemingly rather isotropic system to display the complex structures observed.
Abstract Background Environmental factors, such as weather extremes, have the potential to cause adverse effects on plant biomass quality and quantity. Beyond adversely affecting feedstock yield and composition, which have been extensively studied, environmental factors can have detrimental effects on saccharification and fermentation processes in biofuel production. Only a few studies have evaluated the effect of these factors on biomass deconstruction into biofuel and resulting fuel yields. This field-to-fuel evaluation of various feedstocks requires rigorous coordination of pretreatment, enzymatic hydrolysis, and fermentation experiments. A large number of biomass samples, often in limited quantity, are needed to thoroughly understand the effect of environmental conditions on biofuel production. This requires greater processing and analytical throughput of industrially relevant, high solids loading hydrolysates for fermentation, and led to the need for a laboratory-scale high solids experimentation platform. Results A field-to-fuel platform was developed to provide sufficient volumes of high solids loading enzymatic hydrolysate for fermentation. AFEX pretreatment was conducted in custom pretreatment reactors, followed by high solids enzymatic hydrolysis. To accommodate enzymatic hydrolysis of multiple samples, roller bottles were used to overcome the bottlenecks of mixing and reduced sugar yields at high solids loading, while allowing greater sample throughput than possible in bioreactors. The roller bottle method provided 42–47% greater liquefaction compared to the batch shake flask method for the same solids loading. In fermentation experiments, hydrolysates from roller bottles were fermented more rapidly, with greater xylose consumption, but lower final ethanol yields and CO 2 production than hydrolysates generated with shake flasks. The entire platform was tested and was able to replicate patterns of fermentation inhibition previously observed for experiments conducted in larger-scale reactors and bioreactors, showing divergent fermentation patterns for drought and normal year switchgrass hydrolysates. Conclusion A pipeline of small-scale AFEX pretreatment and roller bottle enzymatic hydrolysis was able to provide adequate quantities of hydrolysate for respirometer fermentation experiments and was able to overcome hydrolysis bottlenecks at high solids loading by obtaining greater liquefaction compared to batch shake flask hydrolysis. Thus, the roller bottle method can be effectively utilized to compare divergent feedstocks and diverse process conditions.
Drilling deep into the subsurface of planetary bodies in the Solar System for samples acquisition enables critical capabilities for future NASA exploration missions in its quest to understand the origins of the Solar System and potentially the search for life. Such planetary bodies as Mars and Europa are key targets for potential missions that would require reaching great depths. Performing drilling while using minimal mass/volume systems and with low energy consumption are the main requirements that are imposed on such technologies. A wireline deep drill, called Auto-Gopher-2, is currently being developed as a joint effort between JPL and Honeybee Robotics Ltd. The Auto-Gopher II is a wireline rotary piezo-percussive deep drilling mechanism that combines formation breaking by rotating and piezoelectric actuator hammering and cuttings removal by rotating a fluted bit. The hammering mechanism is based on the Ultrasonic/Sonic Drill/Corer (USDC) mechanism that has been developed as an adaptable tool for many drilling and coring applications. The USDC uses an intermediate ball-shape free-mass to transform high frequency vibrations of a piezoelectric transducer horn tip into sonic hammering of the drill bit. The lessons learned from the previous studies are being implemented into the development of the Auto-Gopher-II, an autonomous deep wireline drill with integrated cuttings and sample management and drive electronics. Subsystems of the wireline drill are being developed in parallel at JPL and Honeybee Robotics, Ltd. Issues related to the bit and its ability to retain the cuttings for caching and removal are currently being addressed. This paper presents the development efforts of the piezoelectric actuator, cuttings removal and retention flutes and drive electronics.
Simulation of radar returns, full-duplex systems, and signal repeaters require hundreds of ns of programmable broadband radio frequency (RF) delay in the signal path to simulate large distances in the case of radar returns, for signal cancellation in full-duplex, and for isolation from reflections in signal repeaters. However, programmable broadband RF delay has been limited to ones of ns due to challenges in miniaturization with low loss and low power consumption. In this work, we present a 0.2–2 GHz digitally programmable RF delay element based on a time-interleaved multistage switched-capacitor (TIMS-SC) approach. The proposed approach enables hundreds of ns of broadband RF delay by employing sample time expansion in multiple stages of switched-capacitor storage elements. Further, the delay element was implemented in a 45 nm SOI CMOS process and achieves a 2.55–448.6 ns programmable delay range with < 0.12% delay variation across 1.8 GHz of bandwidth at maximum delay, 2.42 ns programmable delay steps, and 330 ns/mm 2 area efficiency. Through the proposed approach, the device shows minimal delay change across a -40 °C to 85 °C temperature range and < 0.25 dB gain variation across delay settings. The device achieves 26 dB gain, 7.4 dB noise figure, and consumes 74 mW from a 1 V supply with an active area of 1.36 mm 2 .
The San Francisco Bay Area's Metropolitan Transportation Commission (MTC) conducted the study in 1981, collecting household and travel information by telephone from 6,209 households in the MTC's nine-county jurisdiction. The sample gave good geographic coverage and provided a good representation of the population groups in the Bay Area. The survey was primarily intended to measure weekday travel; however, the size of the weekend travel sample was sufficient to enable MTC to make inferences about weekend trip generation. Travel days in the sample were spread out evenly over the three-month interviewing period to eliminate seasonal bias.
The Metropolitan Washington Council of Governments/National Capital Region Transportation Planning Board (COG/TPB) periodically conducts regional household travel surveys to monitor changes in daily travel and to gather information on the demographic, socioeconomic, and trip-making characteristics of Washington, D.C.-area residents. Information collected in the 1994 Household Travel Survey was an important component in the development of regional travel demand forecasting models used to predict changes in daily travel in response to current development trends and changes in regional transportation policies and programs. In two waves during the spring and fall of 1994, consultants for COG/TPB conducted a survey of daily travel by persons living in area households. The survey file contains travel information associated with 4,863 households residing in 13 jurisdictions comprising the greater Washington, D.C., region (approximately a 1-in-300 sample). The survey file contains 39,800 internal trip records with respect to the expanded cordon.
Ensuring the efficient engineering of microbially induced calcium carbonate precipitation (MICP) is crucial for a variety of environmental and civil engineering applications, such as soil stabilization and carbon sequestration. Addressing this need, we present a comprehensive multi-scale workflow that begins with the isolation of calcium carbonate-producing microbes from soil samples, followed by metagenomic sequencing and metabolic reconstruction. We then characterize microbial growth phenotypes under diverse nutrient conditions, compare observed growth with metabolic model predictions, and apply the Consistent Reproduction of Phenotype (CROP) algorithm to refine these models. Furthermore, we analyze metabolite consumption and production, and develop a consumer-resource model that is calibrated using time-series measurements of growth rates, pH levels, and calcium carbonate precipitation. The primary benefit of our approach lies in its ability to predict and control MICP outcomes, facilitated by a Bayesian methodology that incorporates priors on initial conditions and parameters. This allows us to compute posteriors by integrating experimental data, and to solve a risk optimization problem under uncertainty to identify nutrient conditions that maximize calcium carbonate production. In contrast to non-Bayesian methods, which fail to quantify uncertainty accurately, our approach provides a more reliable pathway to optimizing nutrient conditions, enhancing the likelihood of achieving desired MICP outcomes. This positions our method as a superior alternative in the quest to improve MICP through engineered microbial consortia.
This document contains all relevant material generated during the authors' summer internship at NREL in 2024. This report shows how to improve energy efficiency of a few code samples by using low-precision data types combined with mixed-precision algorithms. The main applications considered here are (i) linear system solvers using mixed precision, and (ii) neural networks using mixed precision. This report also discusses how programming languages affect energy consumption of algorithms, energy metrics for a code and tools, and the available current software and hardware infrastructure.
The metabolic and environmental factors influencing renal stone formation before, during, and after Space Shuttle flights were assessed. We established the contributing roles of dietary factors in relationship to the urinary risk factors associated with renal stone formation. 24-hr urine samples were collected prior to, during space flight, and following landing. Urinary factors associated with renal stone formation were analyzed and the relative urinary supersaturation ratios of calcium oxalate, calcium phosphate (brushite), sodium urate, struvite and uric acid were calculated. Food and fluid consumption was recorded for a 48-hr period ending with the urine collection. Urinary composition changed during flight to favor the crystallization of stone-forming salts. Factors that contributed to increased potential for stone formation during space flight were significant reductions in urinary pH and increases in urinary calcium. Urinary output and citrate, a potent inhibitor of calcium-containing stones, were slightly reduced during space flight. Dietary intakes were significantly reduced for a number of variables, including fluid, energy, protein, potassium, phosphorus and magnesium. This is the first in-flight characterization of the renal stone forming potential in astronauts. With the examination of urinary components and nutritional factors, it was possible to determine the factors that contributed to increased risk or protected from risk. In spite of the protective components, the negative contributions to renal stone risk predominated and resulted in a urinary environment that favored the supersaturation of stone-forming salts. The importance of the hypercalciuria was noted since renal excretion was high relative to the intake.
Long-term operation of heating, ventilation, and air conditioning (HVAC) systems will eventually lead to a range of HVAC system failures, resulting in excessive energy consumption and maintenance costs. Here, to avoid HVAC malfunctioning, fault detection diagnostic (FDD) is utilized as a common practice. Machine learning methods have lately received considerable interest for FDD analysis of HVAC systems due to their high detection accuracy. Meanwhile, HVAC malfunctions are regarded as rare occurrences, hence normal operating data samples are much more accessible than data samples in faulty and malfunctioning conditions. The dominating frequency of normal operation in HVAC datasets has also led to heavily biased classification algorithms within the literature. Moreover, the focus of previous literature has been on increasing the accuracy of the models which leads to a high number of false positives (misleading alarms) in the system. In order to enhance the performance of diagnostic procedures and fill the mentioned gaps, this study proposes a novel data-driven framework. A bi-level machine learning framework is developed for diagnosing faults in air handling units (AHUs) and rooftop units (RTUs) based on principal component analysis (PCA), time series anomaly detection, and random forest (RF). It is shown that PCA can reduce the dataset dimension with one principal component accounting for 95% of data variance. Also, the random forest could classify the faults with 89% precision for single-zone AHU, 85% precision for RTU, and 79% for multi-zone AHU. By proposing this framework, three persistent challenges are addressed: (I) minimizing false positives; (II) accounting for data imbalance; and (III) normal condition monitoring of equipment.
For one of each of the AVTA's plug-in hybrid electric vehicles, battery electric vehicles, and some hybrid electric vehicles tested in high-mileage courier fleets, the high-voltage traction battery packs were removed from the vehicle and tested at the beginning and end of fleet testing. For some vehicles, batteries also were tested at periodic intervals during fleet testing. Standard reference performance tests were conducted to characterize battery degradation over time. This dataset contains results from two or more rounds of battery tests for 21 distinct year/make/model vehicles (see reference ["INL Advanced Vehicle Testing Activity: On-road Logger and Laboratory Battery Pack Testing Vehicle List"](https://avt.inl.gov/sites/default/files/pdf/reports/DatasetVehicleList.pdf) for full list of vehicles). Each round of battery testing included the "Static Capacity Test" and the "Hybrid Pulse Power Characterization (HPPC) Test", conducted according to test procedures published in the United States Advanced Battery Consortium ["Battery Test Manual For Power-Assist Hybrid Electric Vehicles"](https://www.uscar.org/commands/files_download.php?files_id=57), ["Battery Test Manual For Plug-In Hybrid Electric Vehicles"](https://www.uscar.org/commands/files_download.php?files_id=168), and ["Electric Vehicle Battery Test Procedures Manual"](https://www.uscar.org/commands/files_download.php?files_id=5) prior to the time of testing. These tests were performed by Intertek Testing Services, North America. (This dataset will be shared by API; a small sample of the vehicle battery and test data has been extracted and is available for download while the API is being developed.)
Since the aftermath of the Fukushima Daiichi loss-of-coolant accident, accident-tolerant fuel (ATF) claddings have been developed to improve the coping times in such events. However, the mechanical performance of ATF cladding is crucial in ensuring that it does not negatively impact the mechanical integrity during all other stages of the nuclear fuel cycle, and the validity of the existing safe operating margins must be verified. However, due to the cladding’s tube geometry and textured anisotropy, determination of apparent mechanical properties under certain deformation paths is challenging. In the uniaxial hoop direction, for instance, the measured mechanical stresses include frictional forces caused by loading mandrels or varying deformation paths in the sample during traditional ring tensile testing. This experimental difficulty is exacerbated by the specimen size. However, addressing these challenges enables irradiation separate-effects investigations in which the materials can be inserted in reactors like the High Flux Isotope Reactor, and reducing the material consumption of commercially irradiated material allows for further post-irradiation examinations. Despite the advantages of reduced-scale mechanical testing, any drawbacks from new specimen geometries must be evaluated, and uncertainties from specimen preparation, setup, and analysis methodologies must be understood.
Future long-duration missions face significant challenges maintaining crew health. A critical area is supplying adequate nutrition, as certain vitamins and nutrients in supplied foods and supplements demonstrate substantial degradation during extended storage. To address this issue, we are developing and flight-testing a platform technology that demonstrates in situ microbial production of targeted nutrients over extended mission durations. This 5-year experiment, known as BioNutrients-1, was started on the International Space Station in May 2019. It involves two components: an on-orbit hydration and production experiment; and the development of space-compatible, key bio-manufacturing microorganisms. On-orbit testing utilizes a small “production pack” system that encloses sterile edible growth substrate and desiccated Saccharomyces cerevisiae strains genetically engineered to produce the nutrients beta-carotene or zeaxanthin. On hydration and mixing of the production pack, the organisms revive and grow until limited by the depletion of growth media, hypothetically leading to consistent amounts of biomass and nutrients. In eventual mission applications, the packet contents would be heat treated to inactivate the microorganisms prior to consumption. For these flight experiments, the packet will not be heat treated, but will instead be frozen for return to Earth for analyses. In addition to the production pack trials, 14 different microorganisms/treatments were also delivered to ISS for long-duration storage. These samples will be intermittently returned to Earth and analyzed to determine survival rates and genomics. For this presentation, initial data from returned samples and ground controls will be discussed.
Future long-duration missions face significant challenges maintaining crew health. A critical area is supplying adequate nutrition, as certain vitamins and nutrients in supplied foods and supplements demonstrate substantial degradation during extended storage. To address this issue, we are developing and flight-testing a platform technology that demonstrates in situ microbial production of targeted nutrients over extended mission durations. This 5-year experiment, known as BioNutrients-1, was started on the International Space Station in May 2019. It involves two components: an on-orbit hydration and production experiment; and the development of space-compatible, key bio-manufacturing microorganisms. On-orbit testing utilizes a small "production pack" system that encloses sterile edible growth substrate and desiccated Saccharomyces cerevisiae strains genetically engineered to produce the nutrients beta-carotene or zeaxanthin. On hydration and mixing of the production pack, the organisms revive and grow until limited by the depletion of growth media, hypothetically leading to consistent amounts of biomass and nutrients. In eventual mission applications, the packet contents would be heat treated to inactivate the microorganisms prior to consumption. For these flight experiments, the packet will not be heat treated, but will instead be frozen for return to Earth for analyses. In addition to the production pack trials, 14 different microorganisms/treatments were also delivered to ISS for long-duration storage. These samples will be intermittently returned to Earth and analyzed to determine survival rates and genomics. For this presentation, initial data from returned samples and ground controls will be discussed.
Predictive constitutive equations that connect easy-to-measure transport properties (e.g., viscosity and conductivity) with system performance variables (e.g., power consumption and efficiency) are needed to design advanced thermal and electrical systems. In this work, we explore the use of fluorescent particle-streak analysis to directly measure the local velocity field of a pressure-driven flow, introducing a new Python package (FSVPy) to perform the analysis. Fluorescent streak velocimetry combines high-speed imaging with highly fluorescent particles to produce images that contain fluorescent streaks, whose length and intensity can be related to the local flow velocity. By capturing images throughout the sample volume, the three-dimensional velocity field can be quantified and reconstructed. We demonstrate this technique by characterizing the channel flow profiles of several non-Newtonian fluids: micellar Cetylpyridinium Chloride solution, Carbopol 940, and Polyethylene Glycol. We then explore more complex flows, where significant acceleration is created due to microscale features encountered within the flow. We demonstrate the ability of FSVPy to process streaks of various shapes and use the variable intensity along the streak to extract position-specific velocity measurements from individual images. Thus, we demonstrate that FSVPy is a flexible tool that can be used to extract local velocimetry measurements from a wide variety of fluids and flow conditions.
For one of each of the AVTA's plug-in hybrid electric vehicles, battery electric vehicles, and some hybrid electric vehicles tested in high-mileage courier fleets, the high-voltage traction battery packs were removed from the vehicle and tested at the beginning and end of fleet testing. For some vehicles, batteries also were tested at periodic intervals during fleet testing. Standard reference performance tests were conducted to characterize battery degradation over time. This dataset contains results from two or more rounds of battery tests for 21 distinct year/make/model vehicles (see reference ["INL Advanced Vehicle Testing Activity: On-road Logger and Laboratory Battery Pack Testing Vehicle List"](https://avt.inl.gov/sites/default/files/pdf/reports/DatasetVehicleList.pdf) for full list of vehicles). Each round of battery testing included the "Static Capacity Test" and the "Hybrid Pulse Power Characterization (HPPC) Test", conducted according to test procedures published in the United States Advanced Battery Consortium ["Battery Test Manual For Power-Assist Hybrid Electric Vehicles"](https://www.uscar.org/commands/files_download.php?files_id=57), ["Battery Test Manual For Plug-In Hybrid Electric Vehicles"](https://www.uscar.org/commands/files_download.php?files_id=168), and ["Electric Vehicle Battery Test Procedures Manual"](https://www.uscar.org/commands/files_download.php?files_id=5) prior to the time of testing. These tests were performed by Intertek Testing Services, North America. This dataset is shared by API; a small sample of the vehicle battery and test data has been extracted and is also available for download.