• International Journal of Aeronautical and Space Sciences
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• v.15 no.4
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• pp.419-433
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• 2014

The Mars Exploration Rover Opportunity investigated plains at Meridiani Planum, where laminated sedimentary rocks are present. The Opportunity rover's Athena morphological investigation showed microstructures organized in intertwined filaments of microspherules: a texture we have also found on samples of terrestrial (biogenic) stromatolites and other microbialites. We performed a quantitative image analysis to compare images (n=45) of microbialites with the images (n=30) photographed by the rover (corresponding, approximately, to 25,000/15,000 microstructures). Contours were extracted and morphometric indexes were obtained: geometric and algorithmic complexities, entropy, tortuosity, minimum and maximum diameters. Terrestrial and Martian textures present a multifractal aspect. Mean values and confidence intervals from the Martian images overlapped perfectly with those from the terrestrial samples. The probability of this occurring by chance is $1/2^8$, less than p<0.004. Terrestrial abiogenic pseudostromatolites showed a simple fractal structure and different morphometric values from those of the terrestrial biogenic stromatolite images or Martian images with a less ordered texture (p<0.001). Our work shows the presumptive evidence of microbialites in the Martian outcroppings: i.e., the presence of unicellular life on the ancient Mars.

• The KIPS Transactions:PartC
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• v.8C no.1
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• pp.41-50
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• 2001

With growth of Internet, real time multimedia application services require guarantee of QoS (Quality of Service). However, the existing Internet based on best-effort service is not enough to support those services, so MARS model to support IP multicast over ATM networks and RSVP to provide heterogeneous QoS by resource reservation scheme are proposed. As a simulation result, it is proved that processing delay of MARS is increased and success of resource reservation is decreased as a number of QoS change request of a receiver is increased. Therefore, it is important to provide heterogeneous QoS that distribute a load of MARS caused by convergence of messages and efficiently manage the resource of network as to find out scale of receivers and frequency of QoS change request.

• Journal of computational fluids engineering
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• v.19 no.1
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• pp.64-72
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• 2014

This study aimed at assessing the analysis capability of thermal-hydraulic computer code, MARS for the behaviors of the core make-up tank (CMT). The sensitivity study on the nodalization to simulate the CMT was conducted, and the MARS calculations were compared with KAIST experimental data and RELAP5/MOD3.3 calculations. The 12-node model was fixed through a nodalization study to investigate the effect of the number of nodes in the CMT (2-, 4-, 8-, 12-, 16-node). The sensitivity studies on various parameters, such as water subcooling of the CMT, steam pressure, and natural circulation flow were done. MARS calculations were reasonable in the injection time and the effects of several parameters on the CMT behaviors even though the mesh-dependency should be properly treated for reactor applications.

• Geomechanics and Engineering
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• v.10 no.3
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• pp.269-284
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• 2016

Simplified techniques based on in situ testing methods are commonly used to assess seismic liquefaction potential. Many of these simplified methods were developed by analyzing liquefaction case histories from which the liquefaction boundary (limit state) separating two categories (the occurrence or non-occurrence of liquefaction) is determined. As the liquefaction classification problem is highly nonlinear in nature, it is difficult to develop a comprehensive model using conventional modeling techniques that take into consideration all the independent variables, such as the seismic and soil properties. In this study, a modification of the Multivariate Adaptive Regression Splines (MARS) approach based on Logistic Regression (LR) LR_MARS is used to evaluate seismic liquefaction potential based on actual field records. Three different LR_MARS models were used to analyze three different field liquefaction databases and the results are compared with the neural network approaches. The developed spline functions and the limit state functions obtained reveal that the LR_MARS models can capture and describe the intrinsic, complex relationship between seismic parameters, soil parameters, and the liquefaction potential without having to make any assumptions about the underlying relationship between the various variables. Considering its computational efficiency, simplicity of interpretation, predictive accuracy, its data-driven and adaptive nature and its ability to map the interaction between variables, the use of LR_MARS model in assessing seismic liquefaction potential is promising.

• Nuclear Engineering and Technology
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• v.32 no.3
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• pp.214-226
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• 2000

In an effort to assess the performance of KAERI's coupled 3D kinetics - system T/H code, MARS/MASTER, Exercise III of the OECD main steam line break benchmark is solved. The analysis model of the reference plant, TMI-1 - a 2772 MWth B&W plant, consists of three major components: a core neutronics model involving 241$\times$28 neutronic nodes, a vessel 3D T/H model consisting of 374 hydrodynamic volumes, and a 1D system T/H model containing 157 hydrodynamic volumes. The results show that there is a significant amount of flow mixing occurring in the upper and lower plenum regions and the core power distribution evolves to a highly localized shape due to the presence of a stuck rod, as well as the asymmetric flow distribution. It is judged that MARS/MASTER properly captures these drastic 3-dimensional effects. Comparisons with other results submitted to OECD confirm the accuracy of the MARS/MASTER solution.

• Geomechanics and Engineering
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• v.21 no.6
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• pp.583-598
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• 2020

This study is attempted to propose a new hybrid artificial intelligence model called integrative genetic algorithm with multivariate adaptive regression splines (GA-MARS) for settlement prediction of shallow foundations on sandy soils. In this hybrid model, the evolution algorithm - Genetic Algorithm (GA) was used to search and optimize the hyperparameters of multivariate adaptive regression splines (MARS). For this purpose, a total of 180 experimental data were collected and analyzed from available researches with five-input variables including the bread of foundation (B), length to width (L/B), embedment ratio (D_f/B), foundation net applied pressure (q_net), and average SPT blow count (N_SPT). In further analysis, a new explicit formulation was derived from MARS and its accuracy was compared with four available formulae. The attained results indicated that the proposed GA-MARS model exhibited a more robust and better performance than the available methods.

• Steel and Composite Structures
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• v.33 no.4
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• pp.583-594
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• 2019

In the areas highly exposed to earthquakes, concrete-filled steel tube columns (CFSTCs) are known to provide superior structural aspects such as (i) high strength for good seismic performance (ii) high ductility (iii) enhanced energy absorption (iv) confining pressure to concrete, (v) high section modulus, etc. Numerous studies were reported on behavior of CFSTCs under axial compression loadings. This paper presents an analytical model to predict ultimate load capacity of CFSTCs with circular sections under axial load by using multivariate adaptive regression splines (MARS). MARS is a nonlinear and non-parametric regression methodology. After careful study of literature, 150 comprehensive experimental data presented in the previous studies were examined to prepare a data set and the dependent variables such as geometrical and mechanical properties of circular CFST system have been identified. Basically, MARS model establishes a relation between predictors and dependent variables. Separate regression lines can be formed through the concept of divide and conquers strategy. About 70% of the consolidated data has been used for development of model and the rest of the data has been used for validation of the model. Proper care has been taken such that the input data consists of all ranges of variables. From the studies, it is noted that the predicted ultimate axial load capacity of CFSTCs is found to match with the corresponding experimental observations of literature.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.671-681
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• 2019

This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate ($Na_2SiO_3$) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature ($28^{\circ}C$) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.111-119
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• 2021

Multi-dimensional analysis of reactor safety-KINS standard (MARS-KS) is a thermal-hydraulic code to simulate multiple design basis accidents in reactors. The code has been essential to assess nuclear safety, but has mainly focused on light water reactors, which are in the majority in South Korea. Few previous studies considered pressurized heavy water reactor (PHWR) applications. To verify the code applicability for PHWRs, it is necessary to develop MARS-KS input decks under various transient conditions. This study proposes an input model to simulate small-break loss of coolant accidents for PHWRs. The input model includes major equipment and experimental conditions for test B9802. Calculation results for selected variables during steady-state closely follow test data within ±4%. We adopted the Henry-Fauske model to simulate break flow, with coefficients having similar trends to integrated break mass and trip time for the power supply. Transient calculation results for major thermal-hydraulic factors showed good agreement with experimental data, but further study is required to analyze heat transfer and void condensation inside steam generator u-tubes.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.72-83
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• 2022

This paper presents a numerical investigation of two-phase natural circulation flows established when external reactor vessel cooling is applied to a severe accident of the APR1400 reactor for the in-vessel retention of the core melt. The coolability limit due to external reactor vessel cooling is associated with the natural circulation flow rate around the lower head of the reactor vessel. For an elaborate prediction of the natural circulation flow rate using a thermal-hydraulic system code, MARS-KS1.5, a three-dimensional computational fluid dynamics (CFD) simulation is conducted to estimate the flow rate and pressure distribution of a liquid-state coolant at the brink of significant void generation. The CFD calculation results are used to determine the loss coefficient at major flow junctions, where substantial pressure losses are expected, in the nodalization scheme of the MARS-KS code such that the single-phase flow rate is the same as that predicted via CFD simulations. Subsequently, the MARS-KS analysis is performed for the two-phase natural circulation regime, and the transient behavior of the main thermal-hydraulic variables is investigated.