Elemental Model Research Articles

Prediction of Remaining Life of Turbo Pump Inducer for Spacecraft Using Cumulative Damage Model

In the near future, to operate reusable spacecraft safely and efficiently, it is necessary to have failure prediction technology for reusable rocket engines. Among the components that constitute a rocket engine, the failure of the turbo pump inducer has a significant impact on missions. Therefore, we have been researching to monitor the remaining life of the inducer. This method estimates the fluctuating stress field excited in the inducer section based on the time-series signals from pressure sensors installed upstream. It predicts the remaining life using a Rain flow model to account for high- cycle fatigue (HCF) phenomena. To validate the effectiveness of the proposed method, we attempted to acquire experimental data, particularly for the challenging pressure-stress transfer section where concrete specifications are difficult to define. Through experiments using an elemental model, we demonstrated that a certain degree of remaining life can be predicted based on measurement from the upstream sensor. This indicates that the proposed method is a promising option for solving the remaining life prediction problem of reusable spacecraft.

Effect of Implant-Abutment Connection Type on Stress Distribution in Peri-Implant Bone and Abutment Micromovement: A Three-Dimensional Finite Element Analysis.

This study assessed the effect of implant-abutment connection type on stress distribution in peri-implant bone and abutment micromovement using finite-element analysis (FEA). Dimensions of three implant-abutment designs were measured by a three-dimensional scanner and transferred to SOLIDWORKS. An elemental model was designed using ABAQUS. Each implant was placed in bone at the crestal level. A 100-N load was applied at a 45° angle relative to the longitudinal axis of the implant in the buccolingual direction from the palatal toward the buccal and coronal parts of the abutment. Shear stress, von Mises stress, and micromovement of the abutment relative to the fixture were analyzed. Data were reported qualitatively and quantitatively using ABAQUS. The von Mises stress in all three samples decreased from the crest toward the apical area and was distributed homogenously. Maximum stress concentration was at the most coronal part of the implant body in the midbuccal area. In cancellous and cortical bone, stress decreased from the crest toward the palate and was at its maximum at the midbuccal point in the bone crest. Stress in cortical bone was more homogenous and in cancellous bone was higher. Shear stress was higher in the buccal than in the palatal area, and at its maximum shear stress and equal in the mesiobuccal and distobuccal areas. Micromovement was 4.25 μm in an Astra implant, 5.42 μm in a Intra-Lock implant, and 6.63 μm in an SPI implant. The distribution of von Mises and shear stress was the same in bone around the three implant connection types; however, abutment micomovement differed.

Improvement of steam generator tube failure propagation analysis code LEAP for evaluation of overheating rupture

ABSTRACT As a part of safety assessment or design of steam generators of sodium-cooled fast reactors, it is necessary to evaluate the water leak rate under sodium–water reaction accident. The computer code called LEAP-II calculating a design basis water leak rate during long-time event progress including self-wastage, target-wastage, wastage-type failure propagation, water leak detection, and water/steam blowdown was developed for the prototype fast reactor in the past studies. In this study, a numerical analysis method to predict occurrence of overheating tube rupture was constructed and integrated into this code to expand its application range. The newly constructed method consists of the elemental analysis models for temperature distribution formed by a reacting jet, water-side thermal hydraulics, heat transfer at the tube wall, temperature and stress of the tube, and failure of the tube. Applicability of the method was investigated through the numerical analysis of the experiment on water vapor discharging into liquid sodium pool under the actual condition of the steam generator. The numerical analysis demonstrated that the method could provide the appropriately conservative result on the overheating-rupture-type failure propagation.

Isotopic and elemental profiling to trace the geographic origins of farmed and wild-caught Asian seabass (Lates calcarifer)

Demand for seafood, farmed or wild-caught, is growing globally. Consequently, seafood provenance is increasingly important to regulatory bodies, market chain actors and consumers. The limitations of current seafood provenance methods can be overcome using complementary or standalone nuclear techniques. This study focuses on determining the production method and geographic origin of Asian seabass (Lates calcarifer) using Stable Isotope Analysis (SIA) and X-ray fluorescence (XRF) through Itrax. The data were analysed using three different statistical methods; univariate and multivariate analysis, randomForest and LDA. The SIA model had accuracy of 84% when distinguishing the production methods and geographic origin of the L. calcarifer. The model using elemental analysis from the XRF returned an accuracy of 72%, and a combined SIA and elemental model was 81% accurate in determining provenance. However, the SIA model had two incorrect predictions compared to one incorrect prediction in the elemental model, while the combined model had no incorrectly predicted samples. The results of this study highlight that a combination of both SIA and elemental profiling through Itrax is ideal for seafood provenance.

On the implications of using composite vehicles in choice model prediction

Vehicle choice modelers often use composite alternatives, which are simplified representations of a larger, diverse group of vehicle options—a practice known as choice set aggregation. Although this practice has been justified by computational tractability and data constraints, it can introduce arbitrary changes to choice-share predictions. We isolate and characterize the implications of using composite vehicles for choice prediction, given exogenously determined model parameters. We first identify correction factors needed for composite models to predict choice shares that are consistent with those from models that use the full set of disaggregated elemental alternatives. We then assess the distortion of choice-share predictions under various composite specifications and partial corrections using two case studies based on models in the literature used in transportation and energy policymaking: (1) we examine a logit model without alternative-specific constants (ASCs) and find that the distortion in share predictions due to composite specification is substantial and can be larger than variation due to parameter uncertainty; (2) we examine counterfactual predictions of a nested logit model with ASCs based on the NEMS and LVChoice models and find that composite models using ASCs can mitigate or eliminate distortion in some, but not all, counterfactual scenarios. In particular, the distortion is larger when the scenario significantly affects the differences in elemental membership or utility heterogeneity between composite groups. We provide explicit correction factors for composite models with and without ASCs that can be used to take advantage of the tractability of composite models while ensuring that their choice-share predictions exactly match those of their corresponding elemental models in counterfactual and forecasting scenarios.

A strategy to predict the fracture toughness of steels with a banded ferrite–pearlite structure based on the micromechanics of brittle fracture initiation

This paper presents a strategy to predict the fracture toughness of steels with a banded ferrite–pearlite structure using a new model based on the micromechanics of brittle fracture initiation. The model requires only the (1) ferrite grain size and pearlite band thickness distributions, (2) the stress–strain curve, and (3) the specimen geometry and boundary conditions of the fracture toughness test, without the need for any parameter fittings from the experimental results. The model is based on the multiscale model synthesis approach, consisting of three elemental models: (1) the microstructural spatial distribution, (2) a macroscopic finite element analysis, and (3) the microscopic fracture initiation processes, wherein the respective formulations of the fracture criteria of the three stages are proposed, namely, Stage I: micro-crack formation in shear in the pearlite colony; Stage II: the crack entering the adjacent ferrite grain; and Stage III: the propagation of the crack across ferrite grain boundary. The proposed model was validated by comparing it with the experimental results of five kinds of steels with a range of carbon concentrations, ferrite grain sizes, and pearlite band thicknesses. The predicted and experimental results agreed well for all steel samples and temperatures. In addition, the influence of the microstructure on the fracture toughness was discussed using virtual candidate steels containing various carbon concentrations, ferrite grain sizes, and pearlite band thicknesses. The results demonstrate that the proposed model is an effective and powerful tool for quantitatively predicting the fracture toughness of steel with a banded ferrite–pearlite microstructure.

A Conceptual Framework Review of Gamification Elements on Mobile Marketing Outcomes

The mobile marketing application such as gamification has been used among online marketers which hopes enhance the engagement and purchasing. However, marketing scholars and management practice have paid less attention on how the best gamification elements such as game story, game mechanics, game aesthetics and game technology should affect mobile marketing outcomes. It also claimed to enhance engagement and purchasing but the relationship between customer and games are complex. Therefore, this study intends to extent the knowledge of gamification elements on mobile marketing outcomes (engagement and purchasing). The objective of this study is (i) to develop a comprehensive conceptual framework of gamification elements in mobile marketing outcomes (engagement and purchasing) and (ii) to propose products and consumer moderate the relationship of gamification elements and mobile marketing outcomes. The conceptual framework is proposed on this study with four independent variables of gamification elements (game story, game mechanics, games aesthetics and game technology), two moderator variable (products and consumers) and two dependent variables of mobile marketing outcomes (engagement and purchasing). This study applied Elemental Game Tetrad Model by looking how gamification elements affect the mobile marketing outcomes. The future of the study will contribute the new body of knowledge and area in mobile marketing development.

Summation effects in human learning: evidence from patterning discriminations in goal-tracking.

Participants in two human goal-tracking experiments were simultaneously trained with negative patterning (NP) and positive patterning (PP) discriminations (A+, B+, AB-, C-, D-, CD+). Both elemental and configural models of associative learning predict a PP advantage, such that NP is solved less readily than PP. However, elemental models like the unique cue approach additionally predict responding in AB- trials to be initially stronger than that in A+ and B+ trials due to summation of associative strength. Both experiments revealed a PP advantage and a strong summation effect in AB- trials in the first half of the experiments, irrespective of whether the same US was used for both discriminations (Experiment 1) or two different USs (Experiment 2). We discuss that the correct predictions of the unique cue approach are based on its assumptions of non-normalized and context-independent stimulus processing rather than elemental processing per se.

Period doubling induced by thermal noise amplification in genetic circuits.

Rhythms of life are dictated by oscillations, which take place in a wide rage of biological scales. In bacteria, for example, oscillations have been proven to control many fundamental processes, ranging from gene expression to cell divisions. In genetic circuits, oscillations originate from elemental block such as autorepressors and toggle switches, which produce robust and noise-free cycles with well defined frequency. In some circumstances, the oscillation period of biological functions may double, thus generating bistable behaviors whose ultimate origin is at the basis of intense investigations. Motivated by brain studies, we here study an “elemental” genetic circuit, where a simple nonlinear process interacts with a noisy environment. In the proposed system, nonlinearity naturally arises from the mechanism of cooperative stability, which regulates the concentration of a protein produced during a transcription process. In this elemental model, bistability results from the coherent amplification of environmental fluctuations due to a stochastic resonance of nonlinear origin. This suggests that the period doubling observed in many biological functions might result from the intrinsic interplay between nonlinearity and thermal noise.

The influence of partner cues on the extinction of causal judgments in people.

Studies in laboratory animals have shown that the extinction of a conditioned stimulus, A, is regulated by the associative history of a second stimulus, X, when the two are extinguished in simultaneous compound: An inhibitory X protects A from extinction (Rescorla Learning & Behavior, 31, 124-132, 2003), whereas an excitatory X facilitates, and under some circumstances deepens, the extinction of A (Rescorla Journal of Experimental Psychology: Animal Behavior Processes, 26, 251-260, 2000, Journal of Experimental Psychology: Animal Behavior Processes, 32, 135-144, 2006). In the present study, we used the allergist task to examine whether the extinction of causal judgments in people is similarly regulated by the causal status of co-present stimuli. Experiment 1 showed that a cue trained as a conditioned inhibitor protected a target cue from extinction: The target extinguished in compound with the inhibitor was rated as being more causal of the outcome than was a target extinguished in compound with a control cue lacking inhibitory properties. In contrast, the remaining experiments showed that the extinction of a target cue was regulated by the presence, but not the causal status, of a partner cue: Target cues extinguished in compound were protected from extinction, and no evidence showed that an already extinguished partner conferred more protection (Exp. 2), or that an excitatory partner conferred any less protection (Exps. 2 and 3), or that an excitatory partner deepened the extinction of its already extinguished target. These findings are inconsistent with elemental models that rely on a common error term to explain associative changes in extinction. They are largely, but not completely, consistent with the configural model proposed by Pearce (Psychological Review, 94, 61-73, 1987), which predicts an ordering of levels of protection that was not observed.

Associative accounts of recovery-from-extinction effects

Recovery-from-extinction effects (e.g., spontaneous recovery, renewal, reinstatement, and facilitated reacquisition) have become the focus of much research in recent years. However, despite a great deal of empirical data, there are few theoretical explanations for these effects. This paucity poses a severe limitation on our understanding of these behavioral effects, impedes advances in uncovering neural mechanisms of response recovery, and reduces our potential to prevent relapse after exposure therapy. Toward correcting this oversight, this review takes prominent models of associative learning that have been used in the past and continue to be used today to explain Pavlovian conditioning and extinction, and assesses how each model can be applied to account for recovery-from-extinction effects. The models include the Rescorla–Wagner (1972) model, Mackintosh's (1975) attentional model, Pearce and Hall's (1980) attentional model, Wagner's (1981) SOP model, Pearce's (1987) configural model, McLaren and Mackintosh's (2002) elemental model, and Stout and Miller's (2007) SOCR (comparator hypothesis) model. Each model is assessed for how well it explains or does not explain the various recovery-from-extinction phenomena. We offer some suggestions for how the models might be modified to account for these effects in those instances in which they initially fail.

Biogas Plasticization Coupled Anaerobic Digestion: The Anaerobic Pump Stoichiometry

This paper presents the stoichiometry section of a bioenergetics investigation into the biogas plasticization of wastewater sludge using the Anaerobic Pump (TAP). Three residue samples, an input substrate and two residual products, were collected from two side by side operated AD systems, a conventional continuous flow and stirred reactor, and TAP, and submitted for elemental and calorimetric analyses. The elemental compositions of the residues were fitted to a heterotrophic metabolism model [1] for both systems. To facilitate balanced stoichiometric models, a simple "cell" correction computation separates measured residual composites into "real" residual composition and cell growth (C5H7NO2) components. The elemental data and model results show that the TAP stage II residual composition (C1H0.065O0.0027N0.036) was nearly devoid of hydrogen and oxygen, leaving only fixed carbon and cells grown as the composition of the remaining mass. This quantitative evidence supports prior measurements of very high methane yields from TAP stage II reactor during steady-state experiments [2]. All performance parameters derived from the stoichiometric model(s) showed good agreement with measured steady-state averaged values. These findings are strong evidence that plasticization-disruption (TAP) cycle is the mechanism responsible for the observed increases in methane yield. The accuracy achieved by the stoichiometry models qualifies them for thermodynamic analysis to obtain potentials and bioconversion efficiencies. How applied pressure causes matrix conformation changes triggered by a functional consequence (plasticization and disruption) is this study's essential focus.

Cutting Force and Tool Deflection Predictions for High Speed Machining of Hard to Cut Material

The dimension accuracy and the too life are the major issues of the machining of hard-to-cut materials. To fulfill the requirements of accuracy and tool life needs not only well planning of cutting path but also the proper cutting conditions of cutters. The vibration and deflection of cutters caused by poor selection of cutting conditions can be predicted using models of cutting force and tool deflection. In this paper, a cutting force model considering the effect of tool helical angle and a cantilever beam model of tool deflection were proposed for the high speed machining of hard-to-cut material SKD11. The shearing force, the plowing forces, and the helical angle of cutters are considered in the elemental force model. The material of workpiece, SKD11, studied in this paper is commonly used for the die and mold industries. The cutting constants of the proposed force model are determined via the cutting experiments carried out on a high speed machining center. A dynamometer and a high frequency data acquisition system were used to measure the x-, y-, and z-direction cutting forces. The obtained cutting constants were used to predict the cutting forces and compared with the results obtained from the cutting experiment of verification using cutters with different helical angles. The theoretical and the experimental cutting forces in the x-, y-, and z- direction are in good agreement using flat cutters with 30 and 45 degrees of helical angle. The dimension deviations of the cut surface in the cutting experiment case of tool deflection were measured using a touch probe and an infrared receiver installed on the machining center. The measured average dimension deviation, 0.163mm, is close to the predicted tool deflection, 0.153mm, using the proposed cantilever beam model. The comparisons of the cutting forces and the average of the cut surface dimension deviation are in good agreement and verify the proposed cutting force and the tool deflection models are feasible and useful.

Effects of Diet Intakes on Metal and Electrolyte Distributions in Vital Organs

The intake and concentration of metals and electrolytes from our diet are believed to be affecting our general health, in particular, the proper functions of vital organs. For example, in addition to other genetic and environmental factors, consuming water with high alkalinity for prolonged time is suspected to lead to diseases such as kidney stone. Evidence has been accumulating that excessive metal intakes would lead to organ failures. Once absorbed, minerals and electrolytes can travel freely throughout the body, and distribute at key organ systems such as the brain, lung, kidney, etc. By conducting experiments with animal models (e.g., rats), it is possible to not only determine where the organ distribution of various matrices of elements and minerals but also correlate such matrices with the overall physiological and behavioral status of such models. In this study, information matrices of 30 different elements (including heavy metals and some electrolytes) and their distributions in various vital organs (e.g., brain, lung, kidney, liver, heart, spleen, and uterus) were analyzed as a function of normal dietary intake at adulthood (120 days old). An elemental (metal and electrolyte) distribution model was then formulated based on experimental results. The study has high impact to our understanding of how environmental health would affect our well being. This study would also provide insights on how our diet would affect the accumulations of unwanted elements, such as heavy metals, in our vital organs. The results may help researchers and health practitioner to identify possible links between daily diet (metals and electrolytes) and diseases, and may also lead to a better understanding of diseases associated with aging such as Alzheimer's and Parkinson's diseases, and other neurological disorders.

Pulsed Laser Excited Photothermal Lens Spectrometry of CdSxSe1—x Doped Silica Glasses

Experimental results for photothermal lens measurements are compared to finite elemental analysis models for commercial colored glass filters. Finite elemental analysis software is used to model the photothermal effect by simulating the coupling of heat both within the sample and out to the surroundings. Modeling shows that heat transfer between the glass surface and the air coupling fluid has a significant effect on the predicted time-dependent photothermal lens signals. For comparison with experimental signals, a simple equation based on the finite element analysis result is proposed for accounting for the variance of experimental data where this type of heat coupling situation occurs. The colored glass filters are found to have positive thermo-optical coefficients. The net positive dn/dT of CdSxSe(1-x) doped glass filters is considered to be the consequence of counteracting factors: optical nonlinearity, stress-induced birefringence, and the structural network of glass. Finite element analysis modeling results are also used to correlate experimental measurements of different sample geometries. In particular, the glass samples are compared to ethanol solutions of iron (II) dicylopentadiene in a sample cuvette even though heat transfer is different for these two samples.

Symmetrical generalization decrements: Configural stimulus processing in human contingency learning

Models of associative learning differ in their predictions concerning the symmetry of generalization decrements. Whereas Pearce's (1994) configural model predicts the same response decrement after adding elements to and after removing elements from a previously trained stimulus, elemental models, such as the replaced elements model and Harris's (2006) model, anticipate more of a decrement for removing than for adding elements. In three contingency learning experiments, we manipulated the motion and the spatial arrangement of colored dots in order to induce configural or elemental processing by perceptual grouping. The results reliably showed symmetrical decrements for the added and removed groups. The manipulations of the stimuli had no effect on stimulus processing. This is in line with Pearce's configural model, but it is at variance with the elemental models and previous studies.

Novel carbonaceous coupling products containing sulphur

The coupling of alkali ethynides with CSCl2, SOCl2, or SO2Cl2 results in new carbonaceous polymeric products; their structures were studied by FTIR and XPS spectra, and the assumptions on reaction mechanism were made with respect to the found elemental composition and model calculations. These macromolecular products, obtained in the yields of 80–92%, contain chlorine in the chain terminals, and alkyne sequences along with inserted C=S, S=O or SO2 groups. These inserted sulphur groups contribute to the stability of alkyne sequences as evidenced by FTIR spectra. Soluble thioketone iPr3SiC≡C–CS–C≡CSiiPr3 (2) prepared by similar coupling of iPr3SiC≡CLi (1) with CSCl2 in the yield of 72%, was considered as a support of the suggested coupling mechanism. Similarly monomolecular sulfoxide iPr3SiC≡C–SO–C≡CSiiPr3 (3) was prepared by coupling of iPr3SiC≡CLi (1) with SOCl2 in the yield 75%.

Theoretical Heating Values and Impacts of Pure Compounds and Fuels

Numerous mathematical equations have been created based on data from physical or chemical compositions, proximate or ultimate analysis, and structural analysis of fuel, including combustible elements (i.e., C and H). Elemental composition-based mathematical models are the most reported, with Dulong's equation being among the first available to calculate the calorific value of coal or biomass. However, elemental analysis is expensive and tedious and needs skilled workers to carry out the analysis. It is difficult to make accurately an ultimate analysis of a fuel sample.

Transfer of configural learning between the components of a preexposed stimulus compound: Implications for elemental and configural models of learning.

In 2 experiments, rats received preexposure to 2 compound contexts: AB and CD for the congruent group and AC and BD for the incongruent group. Subsequently, all rats received a configural discrimination in which separate placement in contexts A or B indicated that presentations of stimulus X would be followed by food and presentations of Y would not, and separate placement in contexts C and D indicated that Y would be followed by food and X would not. In both experiments, rats in the congruent group acquired the conditional discrimination more rapidly than those in the incongruent group. These results are inconsistent with conventional associative accounts of either stimulus preexposure effects or configural learning and instead provide support for a connectionist account.

Elemental and configural encoding of the conditioned stimulus.

Five experiments explored the effect of conditioning AB and CD compounds on responding to transfer AD and BC compounds and to elements. These experiments used several conditioning procedures: flavour aversion and instrumental discriminative learning in rats and autoshaping in pigeons. All of the experiments found greater responding to the trained AB and CD than to the transfer AD and BC compounds, a result that agrees with some configural models, but not with an elemental model. All experiments also found greater responding to the transfer AD and BC compounds than to the elements, a result that agrees with elemental, but not configural, models.