Performance evaluation of laterite soil embankment stabilized with bottom ash,coir fiber,and lime

In tropical regions,heavy rainfall induces erosion and shallow landslides on road embankments.Cement-based stabilization methods,common in these regions,contribute to climate change due to their high carbon footprint.This study explored the potential application of coir fiber-reinforced laterite soil-bottom ash mixtures as embankment materials in the tropics.The objective is to enhance engineered embankment slopes'erosion resistance and stability while offering reuse options for industrial byproducts.This study examined various mix designs for unconfined compressive strength(UCS)and permeability,utilizing 30%bottom ash(BA)and 1%coir fiber(CF)with varying sizes ranging from 10 to 40 mm,6%lime,and laterite soil(LS),followed by microstructural analyses.The results demonstrate that the compressive strength increases as the CF length increases to 25 mm.In contrast,permeability increases continuously with increasing CF length.Lime-treated mixtures exhibit superior short-and long-term strength and reduce permeability owing to the formation of cementitious materials,as confirmed by microstructural analyses.A lab-scale slope box was constructed to evaluate the surface erosion of the stabilized laterite soil embankment.Based on the rainfall simulation results,the LS-BA-CF mixtures show better resistance to erosion and deformation compared to untreated LS,especially when lime is added to the top layer.This study provides insights into a sustainable and cost-effective approach for slope stabilization using BA and CF,offering a promising solution for tropical regions susceptible to surface erosion and landslides.

Influence of driving cycles on exhaust emissions and fuel consumption of gasoline passenger car in Bangkok

The influence of different driving cycles on their exhaust emissions and fuel consumption rate of gasoline passenger car was investigated in Bangkok based on the actual measurements obtained from a test vehicle driving on a standard chassis dynamometer. A newly established Bangkok driving cycle （BDC） and the European driving cycle （EDC） which is presently adopted as the legislative cycle for testing automobiles registered in Thailand were used. The newly developed BDC is constructed using the driving characteristic data obtained from the real on-road driving tests along selected traffic routes. A method for selecting appropriate road routes for real driving tests is also introduced. Variations of keyed driving parameters of BDC with different driving cycles were discussed. The results showed that the HC and CO emission factors of BDC are almost two and four times greater than those of EDC, respectively. Although the difference in the NOx emission factor is small, the value from BDC is still greater than that of EDC by 10%. Under BDC, the test vehicle consumes fuel about 25% more than it does under EDC. All these differences are mainly attributed to the greater proportion of idle periods and higher fluctuations of vehicle speed in the BDC cycle. This result indicated that the exhausted emissions and fuel consumption of vehicles obtained from tests under the legislative modal-type driving cycle （EDC） are significantly different from those actually produced under real traffic conditions especially during peak periods.

Effect of cement types, mineral admixtures, and bottom ash on the curing sensitivity of concrete

The curing sensitivity of concrete with cement Types 1, 3, and 5 as well as multiple powders consisting of cement, fly ash, and limestone powder was studied. Bottom ash was also used in the study as an internal curing agent and a partial substi- tution of fine aggregate. The curing sensitivity index was calculated by considering the performances of compressive strength and carbonation depth. Specimens were subjected to two curing conditions： continuously water-cured and continuously air-cured. The results show that cement Type 3 has a lower curing sensitivity, while cement Type 5 increases the curing sensitivity. For the mixes without bottom ash, the use of fly ash increases the curing sensitivity, while limestone powder reduces the curing sen- sRivity of concrete. The use of bottom ash in concrete reduces the curing sensitivity, especially at a lower mass ratio of water to binder. Concrete with limestone powder, together with bottom ash, is least sensitive to curing. The curing sensitivity calculated from carbonation depth also has a similar tendency as that derived by considering compressive strength. From the test results of compressive strength and curing sensitivity, bottom ash has been proven to be an effective internal curing agent.

Simulations of H-Mode Plasmas in Tokamak Using a Complete Core-Edge Modeling in the BALDUR Code

A theory-based model for predicting the pedestal formation in both ion and electron temperatures, and hydrogenic and impurity density is developed and implemented in the 1.5D BALDUR codes for self-consistently simulating H-mode plasma in tokamak. In the simulation, the transports around pedestal, including the electron and ion thermal, hydrogenie and impurity particle transports are calculated using an （Mixed B/gB） model, which is modified to anomalous semi-empirical mixed Bohm/gyro-Bohm include the effects of ωE×B flow shear and magnetic shear. Because of the reduction of transport, the pedestal can be formed. For a preliminary test, this core-edge model is used to simulate the temporal evolution of plasma current, temperature, and density profiles for DIII-D discharges. It is found that the simulations successfully reproduce the experimental results. A statistical analysis, including RMSE and offset, is used to quantify the agreement between the prediction and the corresponding experimental results. The simulation results show an agreement with average RMSE of 11.87%, 14.53%, 7.59% and 12.21% for electron temperature, ion temperature, electron density, and deuterium density profiles, respectively. In addition, it is found that the suppression function developed is effective only in the edge region.

Scaling of the Density Peak with Pellet Injection in ITER

Scalings of the density peak and pellet penetration length in ITER are developed based on simulations using 1.5D BALDUR integrated predictive modeling code. In these simulations, the pellet ablation is described by the Neutral Gas Shielding （NGS） model with grad-B drift effect taken into account. The NGS pellet model is coupled with a plasma core transport model, which is a combination of an MMM95 anomalous transport model and an NCLASS neoclassical transport model. The BALDUR code with a combination of MMM95 and NCLASS models, together with the NGS model, is used to simulate the time evolution of plasma current, ion and electron temperatures, and density profiles for ITER standard type I ELMy H-mode discharges during the pellet injection. As a result, the scaling of the density peak and pellet penetration length at peak density can be established using this set of predictive simulations that covers a wide range of ITER plasma conditions and pellet parameters. The multiple regression technique is utilized in the development of the scalings. It is found that the scaling for density at center is sensitive to both the plasma and pellet parameters; whereas the scalings for density and location of the additional peak are sensitive to the pellet parameters only.

Impact of E×B flow shear stabilization on particle confinement and density peaking at JET

The impact of the E×B flow shear stabilization on particle transport and density peaking at JET is analyzed in the framework of integrated modelling with the CRONOS code.For that purpose,plasmas from a power scan which show a significant increasing of density peaking with the injected neutral beam injection power have been used as a modeling basis.By means of simulations with the quasilinear model GLF23 for the heat and particle transport,a strong link between the particle confinement and E×B flow shear stabilization is found.This is particularly important close to the pedestal region where the particle pinch direction becomes strongly inward for high E×B flow shear values.Such impact introduces some non-negligible deviation from the well-known collisonality dependence of the density peaking,whose general trend has been also obtained in the framework of this modelling by performing pedestal density scans.

CFD-Based Performance Analysis and Experimental Investigation of Design Factors of Vertical Axis Wind Turbines under Low Wind Speed Conditions in Thailand

This paper presents effects of design factors on mechanical performance of Vertical Axis Wind Turbines (VAWTs), and an experimental investigation of optimal VAWT performance under low wind speed conditions in Thailand. Design factors include types of wind turbines, number of blades, types of materials, height-to-radius ratios, and design modifications. Potential VAWT models with different design factors are numerically analyzed within a virtual wind tunnel at various wind speeds by utilizing XflowTM?Computational Fluid Dynamics (CFD) software. The performance curves of each VAWT are obtained as plots of power coefficients against tip speed ratios. It is found that the type of wind turbine, number of blades, and height-to-radius ratio have significant effects on mechanical performance whereas types of materials result in shifts of operating speeds of VAWTs. Accordingly, an optimal VAWT prototype is developed to operate under actual low speed wind conditions. The performance curve from experimental results agrees with the CFD results. The proposed methodology can be used in the computer design of VAWTs to improve mechanical performance before physical fabrication.

Delivery Service Management System Using Google Maps for SMEs in Emerging Countries

This paper proposes a Delivery Service Management(DSM)system for Small and Medium Enterprises(SMEs)that own a delivery fleet of pickup trucks to manage Business-to-Business(B2B)delivery services.The proposed DSM system integrates four systems:Delivery Location Positioning(DLP),Delivery Route Planning(DRP),Arrival Time Prediction(ATP),and Communication and Data Sharing(CDS)systems.These systems are used to pinpoint the delivery locations of customers,plan the delivery route of each truck,predict arrival time(with an interval)at each delivery location,and communicate and share information among stakeholders,respectively.The DSM system deploys Google applications,a GPS tracking system,Google Map APIs,ATP algorithms(embedded in Excel Macros),Line,and Telegram as supporting tools.To improve the accuracy of the ATP system,three tech-niques are applied considering driver behaviors.The proposed DSM system has been implemented in a Thai SME.From the process perspective,the DSM system is a systematic procedure for end-to-end delivery services.It allows the interactions between planner-driver decisions and supporting tools.The supporting tools are simple,can be easily used with little training,and require low capital expenditure.The statistical analysis shows that the ATP algorithm with the three techniques provides high accuracy.Thus,the proposed DSM system is beneficial for practitioners to manage delivery services,especially for SMEs in emerging countries.

A Computer Vision-Based System for Metal Sheet Pick Counting

Inventory counting is crucial to manufacturing industries in terms of inventory management,production,and procurement planning.Many companies currently require workers to manually count and track the status of materials,which are repetitive and non-value-added activities but incur significant costs to the companies as well as mental fatigue to the employees.This research aims to develop a computer vision system that can automate the material counting activity without applying any marker on the material.The type of material of interest is metal sheet,whose shape is simple,a large rectangular shape,yet difficult to detect.The use of computer vision technology can reduce the costs incurred fromthe loss of high-value materials,eliminate repetitive work requirements for skilled labor,and reduce human error.A computer vision system is proposed and tested on a metal sheet picking process formultiple metal sheet stacks in the storage area by using one video camera.Our results show that the proposed computer vision system can count the metal sheet picks under a real situation with a precision of 97.83%and a recall of 100%.

Liquid Phase Exfoliation of 2D Materials and Its ElectrochemicalApplications in the Data-Driven Future

The electrochemical properties of 2D materials,particularly transition metal dichalcogenides(TMDs),hinge ontheir structural and chemical characteristics.To be practicallyviable,achieving large-scale,high-yield production is crucial,ensuring both quality and electrochemical suitability forapplications in energy storage,electrocatalysis,and potentialbasedionic sieving membranes.A prerequisite for success is a deepunderstanding of the synthesis process,forming a critical linkbetween materials synthesis and electrochemical performance.Thisreview extensively examines the liquid-phase exfoliation technique,providing insights into potential advancements and strategies tooptimize the TMDs nanosheet yield while preserving theirelectrochemical attributes.The primary goal is to compiletechniques for enhancing TMDs nanosheet yield through direct liquid-phase exfoliation,considering parameters like solvents,surfactants,centrifugation,and sonication dynamics.Beyond addressing the exfoliation yield,the review emphasizes the potentialimpact of these parameters on the structural and chemical properties of TMD nanosheets,highlighting their pivotal role inelectrochemical applications.Acknowledging evolving research methodologies,the review explores integrating machine learning anddata science as tools for understanding relationships and key characteristics.Envisioned to advance 2D material research,includingthe optimization of graphene,MXenes,and TMDs synthesis for electrochemical applications,this compilation charts a coursetoward data-driven techniques.By bridging experimental and machine learning approaches,it promises to reshape the landscape ofknowledge in electrochemistry,offering a transformative resource for the academic community.

高速公路路面移动激光扫描数据的自动提取

提出了一种基于体像的区域生长方法,用于高速公路环境下移动激光扫描点云的路面自动提取。该方法包括三个主要步骤:构造体素模型;采用基于体素的分割算法提取路面点;利用基于边界的分割算法细化道路边界。为了评价该方法的准确性,我们使用了高速公路平坦和颠簸高坡路面环境下的两个典型试验点的两点云数据集。该算法成功地实现了路面的高精度提取。平均召回率为99.5%,精度为96.3%,F1得分为97.9%。根据所提取的路面,提出了一种路面平整度估计框架。当将路面粗糙度图的结果与视觉图像进行比较时,得到了很好的一致性,说明了所提框架的可行性和有效性。

Multi-function adsorbent-photocatalyst MXene-TiO_(2) composites for removal of enrofloxacin antibiotic from water

MXenes,a new family of two-dimensional transition metal carbides or nitrides,have attracted tremendous attention for various applications due to their unique properties such as good electrical conductivity,hydrophilicity,and ion intercalability.In this work,Ti_(3)C_(2) MXene,or MX,is converted to MX-TiO_(2) composites using a simple and rapid microwave hydrothermal treatment in HCl/NaCl mixture solution that induces formation of fine TiO_(2) particles on the MX parent structure and imparts photocatalytic activity to the resulting MX-TiO_(2) composites.The composites were used for enrofloxacin(ENR),a frequently found contaminating antibiotic,removal from water.The relative amount of the MX and TiO_(2) can be controlled by controlling the hydrothermal temperature resulting in composites with tunable adsorption/photocatalytic properties.NaCl addition was found to play important role as composites synthesized without NaCl could not adsorb enrofloxacin well.Adding NaCl into the hydrothermal treatment causes sodium ions to be simultaneously intercalated into the composite structure,improving ENR adsorption greatly from 1 to 6 mg ENR/g composite.It also slows down the MX to TiO2 conversion leading to a smaller and more uniform distribution of TiO_(2) particles on the structure.MX-TiO_(2)/NaCl composites,which have sodium intercalated in their structures,showed both higher ENR adsorption and photocatalytic activity than composites without NaCl despite the latter having higher TiO2 content.Adsorbed ENR on the composites can be efficiently degraded by free radicals generated from the photoexcited TiO2 particles,leading to high photocatalytic degradation efficiency.This demonstrates the synergetic effect between adsorption and photocatalytic degradation of the synthesized compounds.

A Computer Vision-Based Model for Automatic Motion Time Study

Motion time study is employed by manufacturing industries to determine operation time.An accurate estimate of operation time is crucial for effective process improvement and production planning.Traditional motion time study is conducted by human analysts with stopwatches,which may be exposed to human errors.In this paper,an automated time study model based on computer vision is proposed.The model integrates a convolutional neural network,which analyzes a video of a manual operation to classify work elements in each video frame,with a time study model that automatically estimates the work element times.An experiment is conducted using a grayscale video and a color video of a manual assembly operation.The work element times from the model are statistically compared to the reference work element time values.The result shows no statistical difference among the time data,which clearly demonstrates the effectiveness of the proposed model.

Decision Models for Cargo Container Loading with an Intermediate Hub

In this research,optimization models for air freight forwarders that considers renting air containers and assigning cargos to containers are proposed with the objective to minimize total operating cost.The transportation network consists of an intermediate hub which is used for unloading and sorting cargos before the delivery to destinations.The models provide operational decision at both regions and hub.The proposed models are formulated based on the cargo demand information provided by the forwarders’customers.The models are applicable for air freight forwarders to plan their bookings with airlines with either regular shipment or irregular demand of cargos during peak season.The proposed models take into account constraints related to weight and volume limits of containers and also on constraints related to available containers.The computational results show that the proposed models can be used for practical air cargo planning.A two-phase method is also proposed in order to generate solutions for large instance data sets.The obtained results from the paper also suggest new research directions in this field.

Fuzzy Self-Tuning PID Control of Hydrogen-Driven Pneumatic Artificial Muscle Actuator

In this paper, a fuzzy self-tuning Proportional-Integral-Derivative （PID） control of hydrogen-driven Pneumatic Artificial Muscle （PAM） actuator is presented. With a conventional PID control, non-linear thermodynamics of the hydrogen-driven PAM actuator still highly affects the mechanical actuations itself, causing deyiation of desired tasks. The fuzzy self-tuning PID con- troller is systematically developed so as to achieve dynamic performance targets of the hydrogen-driven PAM actuator. The fuzzy rules based on desired characteristics of closed-loop control are designed to finely tune the PID gains of the controller under different operating conditions. The empirical models and properties of the hydrogen-driven PAM actuator are used as a genuine representation of mechanical actuations. A mass-spring-damper system is applied to the hydrogen-driven PAM actuator as a typical mechanical load during actuations. The results of the implementation show that the viability of the proposed method in actuating the hydrogen-driven PAM under mechanical loads is close to desired oerformance.

AN ENSEMBLE MODEL OF ARIMA AND ANN WITH RESTRICTED BOLTZMANN MACHINE BASED ON DECOMPOSITION OF DISCRETE WAVELET TRANSFORM FOR TIME SERIES FORECASTING

Time series forecasting research area mainly focuses on developing effective forecasting models toimprove prediction accuracy. An ensemble model composed of autoregressive integrated movingaverage （ARIMA）, artificial neural network （ANN）, restricted Boltzmann machines （RBM）, anddiscrete wavelet transform （DWT） is presented in this paper. In the proposed model, DWT firstdecomposes time series into approximation and detail. Then Khashei and Bijari＇s model, which is anensemble model of ARIMA and ANN, is applied to the approximation and detail to extract their bothlinear and nonlinear components and fit the relationship between the components as a function insteadof additive relationship. Furthermore, RBM is used to perform pre-training for generating initialweights and biases based on inputs feature for ANN. Finally, the forecasted approximation and detailare combined to obtain final forecasting. The forecasting capability of the proposed model is testedwith three well-known time series： sunspot, Canadian lynx, exchange rate time series. The predictionperformance is compared to the other six forecasting models. The results indicate that the proposedmodel gives the best performance in all three data sets and all three measures （i.e. MSE, MAE andMAPE）.

Mathematical Modeling of Pneumatic Artificial Muscle Actuation via Hydrogen Driving Metal Hydride-LaNi5

Quantitative understanding of mechanical actuation of intricate Pneumatic Artificial Muscle （PAM） actuators is technically required in control system design for effective real-time implementation. This paper presents mathematical modeling of the PAM driven by hydrogen-gas pressure due to absorption and desorption of metal hydride. Empirical models of both mechanical actuation of industrial PAM and chemical reaction of the metal hydride-LaNi5 are derived systematically where their interac- tions comply with the continuity principle and energy balance in describing actual dynamic behaviors of the PAM actuator （PAM and hydriding/dehydriding-reaction bed）. Simulation studies of mechanical actuation under various loads are conducted so as to present dynamic responses of the PAM actuators. From the promising results, it is intriguing that the heat input for the PAM actuator can be supplied to, or pumped from the reaction bed, in such a way that absorption and desorption of hydrogen gas take place, respectively, in controlling the pressure of hydrogen gas within the PAM actuator. Accordingly, this manipulation results in desired mechanical actuation of the PAM actuator in practical uses.

Soil Organic Carbon Loss and Turnover Resulting from Forest Conversion to Maize Fields in Eastern Thailand

Soil organic carbon(SOC) content and its stable carbon isotopic composition(within the upper 1 m) were measured to determine the e?ect of land-use changes from dry evergreen forest to maize fields in eastern Thailand.Digital land cover maps,derived from aerial photography and satellite images for years 1989,1996,and 2002 were used in association with field surveys and farmer interviews to derive land-use history and to assist in study site selection.Conversion from forest to maize cultivation for the duration of 12 years reduced SOC stocks at the rate of 6.97 Mg C ha-1 year-1.Reduction was most pronounced in the top 10 cm soil layer,which was 47% after 12 years of cultivation.Stable carbon isotope data revealed that the main fraction lost was forest-derived C.Generally low input rates of maize-derived C were not sufficient to maintain SOC at the level prior to forest conversion.After 12 years of continuous maize cultivation,the maize-derived C fraction made up about 20% of total SOC(5 Mg ha-1 of the total 25.31 Mg ha-1).

Mobile sensors’patrol path planning in unobservable border region

Purpose-The border control becomes challenging when a protected region is large and there is a limited number of border patrols.This research paper proposes a novel heuristic-based patrol path planning scheme in order to efficiently patrol with resource scarcity.Design/methodology/approach-The trespasser influencing score,which is determined from the environmental characteristics and trespassing statistic of the region,is used as a heuristic for measuring a chance of approaching a trespasser.The patrol plan is occasionally updated with a new trespassing statistic during a border operation.The performance of the proposed patrol path planning scheme was evaluated and compared with other patrol path planning schemes by the empirical experiment under different scenarios.Findings-The result from the experiment indicates that the proposed patrol planning outperforms other patrol path planning schemes in terms of the trespasser detection rate,when more environment-aware trespassers are in the region.Research limitations/implications-The experiment was conducted through simulated agents in simulated environment,which were assumed to mimic real behavior and environment.Originality/value-This research paper contributes a heuristic-based patrol path planning scheme that applies the environmental characteristics and dynamic statistic of the region,as well as a border surveillance problem model that would be useful for mobile sensor planning in a border surveillance application.