Determination of arsenic species in rice grains using HPLC-ICP-MS

Determination of As species in rice is necessary because inorganic As species (arsenate (As^V) and arsenite (As^III)) are more toxic than organic As (monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA)). This study evaluated the As species in Korean and USA rice grains. Levels were determined using microwave extraction and high performance liquid chromatography coupled with inductively coupled plasma-mass spectrometry (HPLC-ICPMS). Arsenite and DMA were the major species detected in Korean and USA rice. The percentage of inorganic As was 76.94% (54.50–87.86%) for Korean rice and 69.28% (52.94–72.92%) for USA samples. The order and percentage of As species observed in Korean and USA rice were As^III (70%)>DMA (24%)>As^V (5%)>MMA (1%), and As^III (64%)>DMA (28%)>As^V(5%)>MMA (3%), respectively. The As^III concentrations were not significantly different in Korean rice grains, compared to USA grains. The high As^III predominance indicates an elevated toxic effect of As in rice grains and needs further attention.     

Stability assist wheel control of multi-axle all-terrain crane using RLS algorithms with forgetting

Journal of Mechanical Science and Technology - This paper describes stability assist wheel control based on RLS estimation with forgetting in order to improve the dynamic stability of a multi-axle...     

Interoperability of manufacturing applications using the Core Manufacturing Simulation Data (CMSD) standard information model

The goal of this paper is to propose an approach to enhance interoperability between manufacturing applications using the Core Manufacturing Simulation Data Information Model (CMSDIM) in order to streamline design and manufacturing activities throughout the product life cycle. To this end, a system framework required to facilitate such interoperability is first presented. The proposed approach, architecture, and developed translators are then illustrated and demonstrated using two separate case studies. The first case study facilitates design for manufacturing and assembly improvements for the development of new products, allowing for part of a discrete event simulation model of a downstream manufacturing and assembly process to be automatically generated from corresponding product assembly information contained in the lean design engineering software. Conceptual design and development of this case study, which extracts outputs from Design Profit™ lean design software and generates a corresponding discrete event simulation model in ProModel™ for a Nikon® L-100 Camera, is then discussed. The second case study demonstrates interoperability of three applications (order and inventory system, Gantt chart scheduler, and discrete event simulation) for a generic job shop operation. Using the considered case studies, this paper also details and demonstrates the benefits of interoperability enhancement using the CMSDIM, which is an important consideration in any product life cycle. Finally, we discuss how future research opportunities integrating additional manufacturing applications can be used to address intellectual challenges present in our current approach.     

A DDDAMS-based planning and control framework for surveillance and crowd control via UAVs and UGVs

A dynamic data driven adaptive multi-scale simulation (DDDAMS) based planning and control framework is proposed for effective and efficient surveillance and crowd control via UAVs and UGVs. The framework is mainly composed of integrated planner, integrated controller, and decision module for DDDAMS. The integrated planner, which is designed in an agent-based simulation (ABS) environment, devises best control strategies for each function of (1) crowd detection (vision algorithm), (2) crowd tracking (filtering), and (3) UAV/UGV motion planning (graph search algorithm). The integrated controller then controls real UAVs/UGVs for surveillance tasks via (1) sensory data collection and processing, (2) control command generation based on strategies provided by the decision planner for crowd detection, tracking, and motion planning, and (3) control command transmission via radio to the real system. The decision module for DDDAMS enhances computational efficiency of the proposed framework via dynamic switching of fidelity of simulation and information gathering based on the proposed fidelity selection and assignment algorithms. In the experiment, the proposed framework (involving fast-running simulation as well as real-time simulation) is illustrated and demonstrated for a real system represented by hardware-in-the-loop (HIL) real-time simulation integrating real UAVs, simulated UGVs and crowd, and simulated environment (e.g. terrain). Finally, the preliminary results successfully demonstrate the benefit of the proposed dynamic fidelity switching concerning the crowd coverage percentage and computational resource usage (i.e. CPU usage) under cases with two different simulation fidelities.     

Data-driven modeling and simulation framework for material handling systems in coal mines

In coal mining industry, discrete-event simulation has been widely used to support decisions in material handling system (MHS) to achieve premiums on revenues. However, the conventional simulation modeling approach requires extensive expertise of simulation during the modeling phase and lacks flexibility when the MHS structure changes. In this paper, a data-driven modeling and simulation framework is developed for MHS of coal mines to automatically generate a discrete-event simulation model based on current MHS structural and operational data. To this end, a formal information model based on Unified Modeling Language (UML) is first developed to provide MHS structural information for simulation model generation, production information for simulation execution, and output requirement information for defining simulation outputs. Then, Petri net-based model generation procedures are designed and used to automatically generate a simulation model in Arena® based on the simulation inputs conforming to the constructed information model. The proposed framework is demonstrated for one of the largest open-pit coal mines in the USA, and it has been demonstrated that the framework can be used to effectively generate the simulation models that precisely represent MHS of coal mines, and then be used to support various decisions in coal mining such as equipment scheduling.     

Electrochemical behaviors of SnO and Sn anodes for lithium rechargeable batteries

Electrochemical behaviors of Sn and SnO anodes are studied. Charging/discharging curves show irreversible capacities at the first cycle in both Sn and SnO electrodes. The irreversible capacity loss in Sn electrode is due to the incomplete Li removal from Sn after the first cycle. Although the largest capacity loss in SnO electrode is a result from the lithia formation during the first discharge, additional capacity loss arises from the residual Li in metallic Sn owing to the aggregation of Sn upon repeated cycling. Contrary to the previous studies, Li₂₂Sn₅ phase is not observed in the discharge product in Sn and SnO electrodes. The LiSn alloy electrode shows almost 100% cycling efficiency at the first cycle due to the pre-existing Li.     

Analysis and verification of power transmission characteristics of the hydromechanical transmission for agricultural tractors

In this study, we developed a network model of a Hydromechanical transmission (HMT) for tractors. We verified the developed network model using commercial software and analyzed the power transmission characteristics of an HMT-equipped tractor based on the verified network model. We developed a network model considering the power losses of the transmission elements to analyze the power transmission characteristics of the HMT’s main shift. Using this model, we analyzed the power transmission characteristics of the main shift and confirmed that the power of the main shift can be split and circulated depending on the stroke of the Hydrostatic unit (HSU). We then used the model to analyze the HSU stroke, the power transmission efficiency, and the wheel torque, all of which comprise the power transmission characteristics of an HMT-equipped tractor. As a result, the HMT changed the driving speed of the tractor by continuously varying the HSU stroke. The tractor efficiency increased with the driving speed at each mode and decreased after having reached its maximum efficiency. To verify the developed network model, we compared the analysis results of the tractor’s power transmission efficiency and wheel torque with those obtained from commercial software. From the comparative analysis, we confirmed that the power transmission efficiency and wheel torque of the two models coincided. Therefore, we conclude that the developed network model is highly suitable for analyzing the power transmission characteristics of the HMT.