The flat dilatometer test (DMT) has the potential to be a useful tool in the evaluation of liquefaction potential of soils. In practice, it is necessary to carefully examine existing DMT-based methods for evaluating liquefaction potential. We conducted the DMT and cone penetration test (CPT) in high liquefaction potential areas to examine the existing DMT-based methods for liquefaction potential evaluation. Specifically, the DMT and CPT were conducted side-by-side at each of six in-situ sites, and thus it is feasible to utilize those test results to validate the existing DMT-based methods. The DMT parameter, horizontal stress index (K_D), is used as an indicator for estimating liquefaction resistance of soils in terms of cyclic resistance ratio (CRR). The analysis results revealed that the existing K_D-based liquefaction evaluation methods would overestimate the CRR of soils, which leads to overestimation of the factor of safety against liquefaction. Also, the estimations of DMT-K_D values by using the CPT-q_c as well as the correlation between DMT-K_D and CPT-q_c proposed by the previous studies would be significantly smaller than field measurements. The results reflected that further validation of the existing DMT-based methods for liquefaction evaluation is desirable.

In this paper, an efficient model structure composed of a second-order resistance-capacitance network and a simply analytical open circuit voltage versus state of charge (SOC) map is applied to characterize the voltage behavior of a lithium iron phosphate battery for electric vehicles (EVs). As a result, the overpotentials of the battery can be depicted using a second-order circuit network and the model parameterization can be realized under any battery loading profile, without a special characterization experiment. In order to ensure good robustness, extended Kalman filtering is adopted to recursively implement the calibration process. The linearization involved in the calibration algorithm is realized through recurrent derivatives in a recursive form. Validation results show that the recursively calibrated battery model can accurately delineate the battery voltage behavior under two different transient power operating conditions. A comparison with a first-order model indicates that the recursively calibrated second-order model has a comparable accuracy in a major part of the battery SOC range and a better performance when the SOC is relatively low.

For the dynamic demand assessment of bridge structures under ship impact loading, it may be prudent to adopt analytical models which permit rapid analysis with reasonable accuracy. Herein, a nonlinear dynamic macro-element is proposed and implemented to quantify the demand of bridge substructures subjected to ship collisions. In the proposed nonlinear macro-element, a combination of an elastic-plastic spring and a dashpot in parallel is employed to describe the mechanical behavior of ship-bows with strain rate effects. Based on the analytical model using the proposed macro-element, a typical substructure under 5000 deadweight tonnage (DWT) ship collision is discussed. Our analyses indicate that the responses of the structure using the nonlinear macro-element agree with the results from the high resolution model, but the efficiency and feasibility of the proposed method increase significantly in practical applications. Furthermore, comparisons between some current design codes (AASHTO, JTGD60-2004, and TB10002.1-2005) and the developed dynamic analysis method suggest that these design codes may be improved, at least to consider the effect of dynamic amplification on structural demand.

It is essential to manage customers’ diverse desires and to keep manufacturing costs as low as possible for survival in competition and eventually in production. Sharing resources in manufacturing for different products is a vital method of accomplishing this goal. The advantages of using a common process in production are stated in the literature. However, the mathematical models as well as simulation or conceptual models are not sufficient. The main objective of this paper is to develop mathematical models for multiproduct and multistage production under quality and breakdown uncertainties. The idea of the process commonality is incorporated in the proposed models. The models are validated by primary data collected from a Malaysian company and comparison of the timely requirement schedules of earlier MRP II and the proposed models under stable and perfect production environments. An appreciable convergence of the outcomes is observed. However, the proposed models are carrying additional information about the available locations of the parts in a time frame. After validation, the effects of process commonality on cost, capacity and the requirement schedule under uncertainties are examined. It is observed that the use of common processes in manufacturing is always better than the non-commonality scenario in terms of production cost. However, the increase in capacity requirement for commonality designs is higher for an ideal system, while it is less when the system suffers from breakdowns and a quality problem.

The objective of this work is to provide decision-making processes with an updated/real picture of the mobile resources in industrial environments through a constant feedback of information. The combination of identification technologies and wireless sensor networks (WSN) is proposed as a key development to guarantee an accurate and timely supply of online information regarding the localization and tracking of the mobile wireless devices. This approach uses a cooperative and distributed localization system, called ZigID, which is a WSN based on a Zigbee network with radio frequency identification (RFID) active tags as end nodes. The WSN can recover not only the ID information stored at the tags attached to mobile resources, but also any other useful data captured by specific sensors for acceleration, temperature, humidity and fuel status. This paper also shows the development of ZigID, including devices and information flows, as well as its implementation in ground handling operations at the Ciudad Real Central Airport, Spain.

We present a new algorithm for nesting problems. Many equally spaced points are set on a sheet, and a piece is moved to one of the points and rotated by an angle. Both the point and the rotation angle constitute the packing attitude of the piece. We propose a new algorithm named HAPE (Heuristic Algorithm based on the principle of minimum total Potential Energy) to find the optimal packing attitude at which the piece has the lowest center of gravity. In addition, a new technique for polygon overlap testing is proposed which avoids the time-consuming calculation of no-fit-polygon (NFP). The detailed implementation of HAPE is presented and two computational experiments are described. The first experiment is based on a real industrial problem and the second on 11 published benchmark problems. Using a hill-climbing (HC) search method, the proposed algorithm performs well in comparison with other published solutions.

Three optimal linear attitude estimators are proposed for single-point real-time estimation of spacecraft attitude using a geometric approach. The final optimal attitude is represented by modified Rodrigues parameters (MRPs). After introducing incidental right-hand orthogonal coordinates for each pair of measured values, three error vectors are obtained by the use of dot or/and cross products. Corresponding optimality criteria are rigorously quadratic and unconstrained, which do not coincide with Wahba’s constrained criterion. The singularity, which occurs when the principal angle is close to π, can be easily avoided by one proper rotation. Numerical simulations show that the proposed three optimal linear estimators can provide a precision comparable with those complying with the Wahba optimality definition, and have faster computational speed than the famous quaternion estimator (QUEST).