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At least 1,423 records · Page 79

Fuel Property Effects on Knock Propensity and Thermal Efficiency in a Direct-Injection Spark-Ignition Engine

Engine knock remains one of the major barriers to further improvement in thermal efficiency of Direct-Injection Spark-Ignition (DISI) engines. While Research Octane Number and Motor Octane Number are often used as standard rating methods for knock resistance of fuels, the impacts of other fuel properties on knock propensity in modern engines such as heat of vaporization (HoV) and laminar flame speed (LFS) require better understanding in order to co-optimize fuels and engine designs to achieve higher thermal efficiency and lower CO2 emission. In the present study, computational fluid dynamics (CFD) is used to model a boosted DISI engine with a focus on knock prediction and fuel property effects. A level-set G-equation model is employed to capture turbulent premixed combustion, and is coupled with a transported Livengood-Wu (L-W) integral approach to predict autoignition in the unburnt region. A criterion associated with the L-W integral is developed to accurately predict knock onset and knock-limited spark-advance. This model is then applied to a sensitivity analysis of HoV and LFS on knock tendency and thermal efficiency. The pressure-temperature trajectory framework is applied and extended to study the fuel effects on auto-ignition process in the engine. An existing efficiency-based merit function, which is derived from experiments for boosted SI engines, is evaluated and improved based on the current CFD results.

DISI↗

SU-G-206-08: How Should Focal Spot Be Chosen for Optimized CT Imaging with Dose Modulation?

Purpose: To choose the preferred focal spot for achieving optimized CT image quality with balanced tube heating considerations. Methods: An anthropomorphic pelvic phantom was scanned using a GE Discovery CT750 HD at 120 and 140kVp, 0.8s rotation time, and pitch of 0.984. “Smart mA” was enabled to simulate a routine abdomen–pelvis CT scan. Permissible mA values at 120 and 140 kVp were obtained from the Serial Load Rating table (for mimicking a busy CT clinical operation) in the scanner Technical Reference Manual. At each kVp station and two Noise Index levels, the mA Upper Limit was set above/below the permissible mA values. Scanned mA values and focal spot (FS) used were obtained from the DICOM header of each image, and the FS-mA relationship was analyzed. For visual confirmation beyond recorded FS information, a CatPhan with a fat-ring attached for mimicking patient size/shape was scanned at 120kVp. A group of radiologists/physicists compared a pair of CatPhan images qualitatively. Lastly, a number of patient cases were evaluated to confirm the FS-mA relationship. Results: When preset Upper Limit values were above the permissible mA values, the Large FS (labeled 1.2) was used in scans, even if the maximum scanned mA values were much lower than the permissible values at both 120 and 140 kVp. Otherwise the Small FS (labeled 0.7) was used. Visual evaluation of the high contrast module of CatPhan and additional analysis of patient cases further confirmed that the preset Upper Limit determines which focal spot is to be used, not the actual maximum mA value to be scanned. Conclusion: Specific FS can be selected by setting up appropriate mA Upper Limit in a protocol. CT protocols could be optimized by selecting appropriate FS for improving patient image quality, especially benefiting the small size and pediatric patients.

60 APPLIED LIFE SCIENCES↗

Multi-level bandwidth efficient block modulation codes

The multilevel technique is investigated for combining block coding and modulation. There are four parts. In the first part, a formulation is presented for signal sets on which modulation codes are to be constructed. Distance measures on a signal set are defined and their properties are developed. In the second part, a general formulation is presented for multilevel modulation codes in terms of component codes with appropriate Euclidean distances. The distance properties, Euclidean weight distribution and linear structure of multilevel modulation codes are investigated. In the third part, several specific methods for constructing multilevel block modulation codes with interdependency among component codes are proposed. Given a multilevel block modulation code C with no interdependency among the binary component codes, the proposed methods give a multilevel block modulation code C which has the same rate as C, a minimum squared Euclidean distance not less than that of code C, a trellis diagram with the same number of states as that of C and a smaller number of nearest neighbor codewords than that of C. In the last part, error performance of block modulation codes is analyzed for an AWGN channel based on soft-decision maximum likelihood decoding. Error probabilities of some specific codes are evaluated based on their Euclidean weight distributions and simulation results.

Lin, Shu↗

Identifying Differential Equations in Fourier Domain (FourierIdent)

We investigate identifying differential equations in the frequency domain. Fourier analysis is an important tool in theoretical analysis and numerical solvers of differential equations, yet there is limited work in exploring this connection in the identification of differential equations. This paper aims to identify the underlying differential equation in the frequency domain, from a given single realization of the differential equation perturbed by noise. Such setting imposes difficulties which are different from other identification methods where computation is carried out in the physical domain. We propose several ways to mitigate the challenges arising from noise in data and large differences in the magnitudes of frequency responses. The main takeaways are that identifying differential equations solely in the frequency domain is challenging, the method we propose is based on a form of domain partitions in the frequency domain, and this method shows benefits for complex data even with high level of noise. We introduce a Fourier feature denoising, and define the meaningful data region and the core regions of features to reduce the effect of noise in the frequency domain and to enhance the accuracy in coefficient identification. The proposed method is tested on various differential equations with linear, nonlinear, and high-order derivative feature terms, and shows advantages on complex data with many frequency modes, even under high level of noise.

97 MATHEMATICS AND COMPUTING↗

Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure

Coarse-grained modeling can be used to explore general theories that are independent of specific chemical detail. In this paper, we present cg_openmm, a Python-based simulation framework for modeling coarse-grained hetero-oligomers and screening them for structural and thermodynamic characteristics of cooperative secondary structures. cg_openmm facilitates the building of coarse-grained topology and random starting configurations, setup of GPU-accelerated replica exchange molecular dynamics simulations with the OpenMM software package, and features a suite of postprocessing thermodynamic and structural analysis tools. In particular, native contact analysis, heat capacity calculations, and free energy of folding calculations are used to identify and characterize cooperative folding transitions and stable secondary structures. In this work, we demonstrate the capabilities of cg_openmm on a simple 1–1 Lennard-Jones coarse-grained model, in which each residue contains 1 backbone and 1 side-chain bead. By scanning both nonbonded and bonded force-field parameter spaces at the coarse-grained level, we identify and characterize sets of parameters which result in the formation of stable helices through cooperative folding transitions. Furthermore, we show that the geometries and stabilities of these helices can be tuned by manipulating the force-field parameters.

36 MATERIALS SCIENCE↗

Projected Commutator DIIS Method for Accelerating Hybrid Functional Electronic Structure Calculations

The commutator direct inversion of the iterative subspace (commutator DIIS or C-DIIS) method developed by Pulay is an efficient and the most widely used scheme in quantum chemistry to accelerate the convergence of self-consistent field (SCF) iterations in Hartree–Fock theory and Kohn–Sham density functional theory. The C-DIIS method requires the explicit storage of the density matrix, the Fock matrix, and the commutator matrix. Hence, the method can only be used for systems with a relatively small basis set, such as the Gaussian basis set. We develop a new method that enables the C-DIIS method to be efficiently employed in electronic structure calculations with a large basis set such as planewaves for the first time. The key ingredient is the projection of both the density matrix and the commutator matrix to an auxiliary matrix called the gauge-fixing matrix. The resulting projected commutator-DIIS method (PC-DIIS) only operates on matrices of the same dimension as that consists of Kohn–Sham orbitals. The cost of the method is comparable to that of standard charge mixing schemes used in large basis set calculations. The PC-DIIS method is gauge-invariant, which guarantees that its performance is invariant with respect to any unitary transformation of the Kohn–Sham orbitals. We demonstrate that the PC-DIIS method can be viewed as an extension of an iterative eigensolver for nonlinear problems. We use the PC-DIIS method for accelerating Kohn–Sham density functional theory calculations with hybrid exchange–correlation functionals, and demonstrate its superior performance compared to the commonly used nested two-level SCF iteration procedure. Furthermore, we demonstrate that in the context of ab initio molecular dynamics (MD) simulation with hybrid functionals one can extrapolate the gauge-fixing matrix to achieve the goal of extrapolating the entire density matrix implicitly along the MD trajectory. Here, numerical results indicate that the new method significantly reduces the number of SCF iterations per MD step, compared to the commonly used strategy of extrapolating the electron density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First-Principles Integrated Adsorption Modeling for Selective Capture of Uranium from Seawater by Polyamidoxime Sorbent Materials

Nuclear power is a relatively carbon-free energy source that has the capacity to be utilized today in an effort to stem the tides of global warming. The growing demand for nuclear energy, however, could put significant strain on our uranium ore resources, and the mining activities utilized to extract that ore can leave behind long-term environmental damage. A potential solution to enhance the supply of uranium fuel is to recover uranium from seawater using amidoximated adsorbent fibers. This technology has been studied for decades but is currently plagued by the material’s relatively poor selectivity of uranium over its main competitor vanadium. In this work, we investigate the binding schemes between uranium, vanadium, and the amidoxime functional groups on the adsorbent surface. Using quantum chemical methods, binding strengths are approximated for a set of complexation reactions between uranium and vanadium with amidoxime functionalities. Those approximations are then coupled with a comprehensive aqueous adsorption model developed in this work to simulate the adsorption of uranium and vanadium under laboratory conditions. Experimental adsorption studies with uranium and vanadium over a wide pH range are performed, and the data collected are compared against simulation results to validate the model. It was found that coupling ab initio calculations with process level adsorption modeling provides accurate predictions of the adsorption capacity and selectivity of the sorbent materials. Furthermore, this work demonstrates that this multiscale modeling paradigm could be utilized to aid in the selection of superior ligands or ligand compositions for the selective capture of metal ions. Furthermore, this first-principles integrated modeling approach opens the door to the in silico design of next-generation adsorbents with potentially superior efficiency and selectivity for uranium over vanadium in seawater.

36 MATERIALS SCIENCE↗

EC-Bench: A Benchmark for Enzyme Commission Number Prediction

Enzymes are proteins that catalyze specific biochemical reactions in cells. Enzyme Commission (EC) numbers are used to annotate enzymes in a four-level hierarchy that classifies enzymes based on the specific chemical reactions they catalyze. Accurate EC number prediction is essential for understanding enzyme functions. Despite the availability of numerous methods for predicting EC numbers from protein sequences, there is no unified framework for evaluating and studying such methods systematically. This gap limits the ability of the community to identify the most effective approaches for enzyme annotation. We introduce EC-Bench, a benchmark for EC number prediction, consisting of 1) an initial representative set of existing methods (including homology-based, deep learning, contrastive learning, and language model methods), 2) existing and novel accuracy and efficiency performance metrics, and 3) selected datasets to allow for comprehensive comparative study. EC-Bench is open-source and provides a framework for researchers to not only compare among existing methods objectively under uniform conditions, but also to introduce and effectively evaluate performance of new methods in a comparative framework. To demonstrate the utility of EC-Bench, we perform extensive experimentation to compare the existing EC number prediction methods and establish their advantages and disadvantages in a variety of prediction tasks, namely “exact EC number prediction”, “EC number completion” and (partial or additional) “EC number recommendation”. We find wide variation in the performance of different methods, but also subtle but potentially useful differences in the performance of different methods across tasks and for different parts of the EC hierarchy.

59 BASIC BIOLOGICAL SCIENCES↗

A Radio Emission Analysis of Classical Nova V351 Pup (1991)

Previously, Nova Puppis 1991 (V351 Pup) was measured to host one of the most massive ejections claimed in the literature. Multi-frequency radio detections from one epoch were published for this nova in the 1990's; and yet, the remaining data collected by the Karl G. Jansky Very Large Array (VLA) have remained unpublished. In this paper, we analyze the remaining unpublished data sets for V351 Pup at frequencies of 4.9, 8.4, 14.9, and 22.5 GHz. We fit the resulting light curve to a model of expanding thermal ejecta, under the assumption that the radio emission is dominated by free–free radiation and accounting for high levels of clumping in the ejecta. Images of V351 Pup in both the radio (from the VLA) and Hα+[N ii] (from Hubble Space Telescope) exhibit no aspherical structure, strengthening our assumption of spherical symmetry. From expansion parallax methods, we estimate the distance to V351 Pup to be 5.0 ± 1.5 kpc. Our light-curve fit yields a value of log{sub 10}(M{sub ej})=−5.2±0.7 M{sub ⊙} for the ejecta mass, implying that V351 Pup is on the low end of expectations for ejecta mass from classical novae. A comparison between our derived ejecta mass and theoretical models gives evidence for a very massive (1.25 M{sub ⊙}) white dwarf, which is consistent with spectroscopic evidence for an oxygen–neon white dwarf.

79 ASTRONOMY AND ASTROPHYSICS↗

New Suns in the Cosmos. IV. The Multifractal Nature of Stellar Magnetic Activity in Kepler Cool Stars

In the present study, we investigate the multifractal nature of a long-cadence time series observed by the Kepler mission for a sample of 34 M dwarf stars and the Sun in its active phase. Using the Multifractal Detrending Moving Average algorithm, which enables the detection of multifractality in nonstationary time series, we define a set of multifractal indices based on the multifractal spectrum profile as a measure of the level of stellar magnetic activity. This set of indices is given by the (A, Δα, C, H)-quartet, where A, Δα, and C are related to geometric features from the multifractal spectrum and the global Hurst exponent H describes the global structure and memorability of time series dynamics. As a test, we measure these indices and compare them with a magnetic index defined as S {sub ph} and verify the degree of correlation among them. First, we apply the Poincaré plot method and find a strong correlation between the 〈S{sub ph}〉 index and one of the descriptors that emerges from this method. As a result, we find that this index is strongly correlated with long-term features of the signal. From the multifractal perspective, the 〈S{sub ph}〉 index is also strongly linked to the geometric properties of the multifractal spectrum except for the H index. Furthermore, our results emphasize that the rotation period of stars is scaled by the H index, which is consistent with Skumanich’s relationship. Finally, our approach suggests that the H index may be related to the evolution of stellar angular momentum and a star’s magnetic properties.

79 ASTRONOMY AND ASTROPHYSICS↗

Characterization of fault recovery through fault injection on FTMP

The development of fault-injection procedures and statistical analysis techniques to characterize the fault recovery of fault-tolerant systems is described. Pin-level fault-injection was conducted on a fault-tolerant microprocessor computer in order to generate data to assess the utility of current fault-injection sampling methods. The validity of common reliability-modeling assumptions concerning the statistical distribution of recovery times is investigated. A multiple comparison analysis for detecting behavior variations, and a distribution fitting for determining the best fit for the data were conducted. It is observed that the detection behavior is not homogeneous across all data sets, and that none of the factors under experimental control can account for the observed groupings of behavior. It is determined that no single distribution fits all the data sets, and that stratified random sampling and statistically robust parameter-estimation techniques are required to characterize fault detection time.

Finelli, George B.↗

Algebraic multigrid

The state of the art in algebraic multgrid (AMG) methods is discussed. The interaction between the relaxation process and the coarse grid correction necessary for proper behavior of the solution probes is discussed in detail. Sufficient conditions on relaxation and interpolation for the convergence of the V-cycle are given. The relaxation used in AMG, what smoothing means in an algebraic setting, and how it relates to the existing theory are considered. Some properties of the coarse grid operator are discussed, and results on the convergence of two-level and multilevel convergence are given. Details of an algorithm particularly studied for problems obtained by discretizing a single elliptic, second order partial differential equation are given. Results of experiments with such problems using both finite difference and finite element discretizations are presented.

Ruge, J. W.↗

Subtask 1.5 – CO2 Injection Monitoring with an Optimized Scalable, Automated, Semipermanent Seismic Array

The scalable, automated, semipermanent seismic array (SASSA) method is a flexible and relatively cost-effective surface geophysical method for regular time-lapse monitoring of the movement of injected carbon dioxide (CO2) in a reservoir for CO2 enhanced oil recovery (EOR) or geologic CO2 storage operations. It has the advantages of a low-environmental-footprint while monitoring regions of a reservoir from the surface without the need for a regular grid distribution of receivers. Automated data collection is possible. As only time-lapse amplitude changes at the reservoir level due to CO2 movement within the reservoir are monitored, the turnaround time to deliver results from the SASSA method can be short, without the need for long, time-consuming data-processing workflows. As data is collected and processed, incremental information can be provided to the field operator. The Energy & Environmental Research Center (EERC) conducted a SASSA field test from September 2018 to November 2020 in a portion of the Bell Creek Field in Montana, which implemented new CO2 EOR field activities during the study period. Lessons learned from a proof-of-concept study were incorporated to improve the data quality of the SASSA method and demonstrate the viability of the technology. The EERC implemented several enhancements to improve data quality, including 1) an iterative survey design, which allowed placing the receivers in strategic locations where the movement of the CO2 in the reservoir could be tracked with minimum interference by the cultural noise in the study area; 2) the use of powerful seismic sources in the form of surface orbital vibrators, and 3) data acquisition during optimal periods. History-matched reservoir simulation was performed to predict gas saturation and pressure response induced by CO2 injection in the study area. The results were compared with the SASSA-measured responses to CO2 injection as a partial validation technique. A match between the two methods was observed for most of the SASSA points predicted to have intersected a CO2 saturation change. The validated results provide confidence that the SASSA method can be used independently as a CO2 saturation monitoring technique. As data are collected and processed, incremental information can be provided to the field operator. The critical components of the SASSA workflow for a successful application of the method are the following: Iterative survey design with information about CO2 injection activities from the oilfield operator. A detailed CO2 injection plan is the key driver to select the strategic monitoring location of the SASSA sensors. After this information is incorporated in the initial distribution of sources and receivers in the study area, high-resolution satellite images are used to identify ground locations not affected by cultural noise sources, such as power lines, pipelines/flow lines, or roadways. In the next iteration of the survey design, a scouting trip to the study area is needed to understand more details of the noise sources identified in the previous step and the intensity of the field activities that can also generate noise during the monitoring. Integrating the information from the scouting trip into the survey design to select the optimum source and receiver locations is the final step. Noise attenuation. The variety of noise types during seismic monitoring of an oil field is enormous. Tailored noise characterization and processing at a node-by-node level can enhance the performance and sensitivity of the SASSA technique. Future advancements that could improve the efficiency and application of the SASSA technology include: Gaining a better understanding of the noise field produced by the seismic source to aid the choice of receiver location. Surface noise from the source can overwhelm the small signal changes due to CO2 that the SASSA method measures. Improved data-processing workflow to automatically analyze and adapt to dynamic noise conditions associated with industrial settings. This subtask was funded through the EERC–DOE Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE- FE0024233.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Development of disposal container designs for disposal of high level waste and legacy spent fuel in the UK - 15471

Radioactive Waste Management Limited (RWM), a fully owned subsidiary of the Nuclear Decommissioning Authority (NDA), is responsible for the implementation of geological disposal in the UK. Three illustrative concepts of a geological disposal facility (GDF), corresponding to three generic geological environments - higher strength rock, lower strength sedimentary rock and evaporite rock - have been developed to demonstrate the viability of geological disposal of intermediate level waste, high level waste and spent fuel. It is envisaged that HLW which has been encapsulated in Waste Vitrification Plant (WVP) canisters, advanced gas-cooled reactor (AGR) SF which has been stripped of their spacers and packaged into slotted fuel cans, and PWR SF will be packaged into disposal containers for disposal. A set of schematic designs of these disposal containers was developed in the late 2000's. The design concept for the higher strength rock environment was based on the joint Posiva/SKB disposal container design, and the design concept for the lower strength sedimentary rock and evaporate rock illustrative environments was based on the disposal container concept from Switzerland's National Cooperative for the Disposal of Radioactive Waste (Nagra). The size, mass and dimensions of the disposal containers in the scheme designs vary significantly. The construction method and the lid closing method also vary between the disposal containers for the different waste contents. A design study has indicated that optimization of the number of HLW WVP canisters and the number of AGR slotted fuel cans in the disposal containers, standardizing construction method and closure arrangement across the containers for each geology type, providing handling features at both ends of the disposal container, and balancing of shielding around the containers, could bring significant advantage to the overall GDF programme by reducing the number of disposal containers, reducing GDF footprint, and reducing the extent of excavations, spoil generated and materials that are required for construction. A project to develop the scheme designs to conceptual level was carried in 2011 to 2013. In this project, the above changes were taken into account, technical underpinning of the designs was carried out and manufacturing method was considered. Two disposal container variants for different host rock environments have been developed: - Variant 1, for compatibility with the higher strength rock illustrative disposal system design. This is constructed from copper, with a cast iron insert and is based on the joint Posiva/SKB disposal container design. - Variant 2, for compatibility with the lower strength sedimentary rock and evaporite rock illustrative disposal system designs. This is a steel container based on the NAGRA disposal container design. Each variant has three internal configurations to accommodate 3 HLW vitrified canisters, 16 consolidated cans of AGR SF and 4 PWR spent fuel assemblies. These designs have been shown to bring significant benefit to the GDF designs, bringing a significant reduction to the operating programme and GDF programme cost, including reducing the number of disposal containers by 33% for HLW, 50% for AGR SF and reducing the size of the GDF footprint by 25%. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Gas breakthrough and emission through unsaturated compacted clay in landfill final cover

Highlights: • Explore feasibility of unsaturated clay as a gas barrier in landfill cover. • Gas breakthrough pressure increases with clay thickness and degree of saturation. • Gas emission rate decreases with clay thickness and degree of saturation. • A 0.6 m-thick clay layer may be sufficient to meet gas emission rate limit. - Abstract: Determination of gas transport parameters in compacted clay plays a vital role for evaluating the effectiveness of soil barriers. The gas breakthrough pressure has been widely studied for saturated swelling clay buffer commonly used in high-level radioactive waste disposal facility where the generated gas pressure is very high (in the order of MPa). However, compacted clay in landfill cover is usually unsaturated and the generated landfill gas pressure is normally low (typically less than 10 kPa). Furthermore, effects of clay thickness and degree of saturation on gas breakthrough and emission rate in the context of unsaturated landfill cover has not been quantitatively investigated in previous studies. The feasibility of using unsaturated compacted clay as gas barrier in landfill covers is thus worthwhile to be explored over a wide range of landfill gas pressures under various degrees of saturation and clay thicknesses. In this study, to evaluate the effectiveness of unsaturated compacted clay to minimize gas emission, one-dimensional soil column tests were carried out on unsaturated compacted clay to determine gas breakthrough pressures at ultimate limit state (high pressure range) and gas emission rates at serviceability limit state (low pressure range). Various degrees of saturation and thicknesses of unsaturated clay sample were considered. Moreover, numerical simulations were carried out using a coupled gas–water flow finite element program (CODE-BRIGHT) to better understand the experimental results by extending the clay thickness and varying the degree of saturation to a broader range that is typical at different climate conditions. The results of experimental study and numerical simulation reveal that as the degree of saturation and thickness of clay increase, the gas breakthrough pressure increases but the gas emission rate decreases significantly. Under a gas pressure of 10 kPa (the upper bound limit of typical landfill gas pressure), a 0.6 m or thicker compacted clay is able to prevent gas breakthrough at degree of saturation of 60% or above (in humid regions). Furthermore, to meet the limit of gas emission rate set by the Australian guideline, a 0.6 m-thick clay layer may be sufficient even at low degree of saturation (i.e., 10% like in arid regions)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Exploring Data Set Bias and Decision Support with Predictive Uncertainty Through Bayesian Approximations and Convolutional Neural Networks

Individual seismic catalogs can contain multiscale observations from fault level to global scales and associated waveforms from discrete events reflect crustal structure across many different scales and locations. Seismic network aperture, geographic location, and observation distance may not provide informative guidance or intuition on how different catalogs will behave across models trained under different conditions. We rely on uncertainty to provide guardrails for when to trust model decisions, but understanding when our uncertainty is trustworthy is an open challenge. Here, in this work, we explore Bayesian approximation methods for assigning predictive uncertainty in seismic event classification problems. We find that computationally expensive Bayesian approximations do not outperform simple ensemble methods. We also find that when exploiting multiple seismic event catalogs, joint training with data from all the catalogs combined with Bayesian approximations and supervised training for classification can obscure bias and result in less robust uncertainty while also not providing substantial performance benefits compared to training individual models for each catalog.

58 GEOSCIENCES↗

The establisment of an achievement test for determination of primary teachers’ knowledge level of earthquake

In this study it was aimed to improve an academic achievement test to establish the students’ knowledge about the earthquake and the ways of protection from earthquakes. In the method of this study, the steps that Webb (1994) was created to improve an academic achievement test for a unit were followed. In the developmental process of multiple choice test having 25 questions, was prepared to measure the pre-service teachers’ knowledge levels about the earthquake and the ways of protection from earthquakes. The multiple choice test was presented to view of six academics (one of them was from geographic field and five of them were science educator) and two expert teachers in science Prepared test was applied to 93 pre-service teachers studying in elementary education department in 2014-2015 academic years. As a result of validity and reliability of the study, the test was composed of 20 items. As a result of these applications, Pearson Moments Multiplication half-reliability coefficient was found to be 0.94. When this value is adjusted according to Spearman Brown reliability coefficient the reliability coefficient was set at 0.97.

42 ENGINEERING↗

Opportunities and data requirements for data-driven prognostics and health management in liquid hydrogen storage systems

During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.

08 HYDROGEN↗