Estimation of directional wave spectra and hull structural responses based on measured hull data on 14,000 TEU large container ships

To ensure hull structural strength of container ships in association with their increase in size, it is very important to grasp the hull stress histories all over the hull structure in actual sea state. However, ordinary hull stress monitoring systems are insufficient for this purpose because of the small number of stress sensors actually practicable. Therefore, in this paper, we discuss an approach to reproduce the hull stress responses which are not measured based on the estimated wave spectrum from the limited measurement data. To achieve this, we introduce a new model to estimate directional wave spectra based on measured ship stress responses and ship response functions, and further we estimate other ship responses using the model. To model an arbitrarily shaped directional wave distribution, the 360° direction is discretized into 36 directions of 10-degree intervals instead of using a directional distribution function, and in each direction, the wave spectrum is represented using the Ochi (3P) spectrum with three parameters (average wave period, significant wave height, and kurtosis). The authors discuss the evaluation results based on two stress response combinations, and a comparison is made between the sea state estimates made by the proposed method and the ocean wave hindcast database (JWA). Furthermore, by comparing the significant values and the spectra of the measured response of the ship with the estimated response based on both the estimated sea state by the proposed method and the hindcast sea state, the accuracies of the proposed method and the hindcast method are discussed in terms of ship stress estimation at non-instrumented locations.     

Complete Modeling for Systems of a Marine Diesel Engine

This paper presents a simulator model of a marine diesel engine based on physical, semi-physical, mathematical and thermodynamic equations, which allows fast predictive simulations. The whole engine sy...     

Improving airline fuel efficiency via fuel burn prediction and uncertainty estimation

Reducing fuel consumption is a unifying goal across the aviation industry. One fuel-saving opportunity for airlines is the possibility of reducing discretionary fuel loading by dispatchers. In this study, we propose a novel discretionary fuel estimation approach that can assist dispatchers with better discretionary fuel loading decisions. Based on the analysis on our study airline, our approach is found to substantially reduce unnecessary discretionary fuel loading while maintaining the same safety level compared to the current fuel loading practice. The idea is that by providing dispatchers with more accurate information and better recommendations derived from flight records, unnecessary fuel loading and corresponding cost-to-carry could both be reduced. We apply ensemble learning techniques to improve fuel burn prediction and construct prediction intervals (PIs) to capture the uncertainty of model predictions. The upper bound of a PI can then be used for discretionary fuel loading. The potential benefit of this approach is estimated to be $61.5 million in fuel savings and 428 million kg of CO₂ reduction per year for our study airline. This study also builds a link between discretionary fuel estimation and aviation system predictability in which the proposed models can also be used to predict benefits from reduced fuel loading enabled by improved Air Traffic Management (ATM) targeting on improved system predictability.     

Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates

Data from connected probe vehicles can be critical in estimating road traffic conditions. Unfortunately, current available data is usually sparse due to the low reporting frequency and the low penetration rate of probe vehicles. To help fill the gaps in data, this paper presents an approach for estimating the maximum likelihood trajectory (MLT) of a probe vehicle in between two data updates on arterial roads. A public data feed from transit buses in the city of San Francisco is used as an example data source. Low frequency updates (at every 200 m or 90 s) leaves much to be inferred. We first estimate travel time statistics along the road and queue patterns at intersections from historical probe data. The path is divided into short segments, and an Expectation Maximization (EM) algorithm is proposed for allocating travel time statistics to each segment. Then the trajectory with the maximum likelihood is generated based on segment travel time statistics. The results are compared with high frequency ground truth data in multiple scenarios, which demonstrate the effectiveness of the proposed approach, in estimating both the trajectory while moving and the stop positions and durations at intersections.     

Estimating vehicle speed with embedded inertial sensors

Pavements were instrumented with inertial sensors, and the possibility of estimating the speed of a passing vehicle was investigated numerically and experimentally from the measurements of two embedded accelerometers. The sensors were spaced apart in the travel direction, and subsequently the speed was directly related to the time delay between the received signals. No assumption was made regarding the vehicle and pavement properties. Model accelerations were presented, studied, and contrasted against field measurements; the latter were shown to be dominated by random vibration sources. Two calculation techniques were offered and applied to handle the noisy data. The first was based on time-centroids, and the second was based on cross-correlation with kernel presmoothing. The overall concept is deemed promising not only for inferring speeds but also for extracting additional traffic characteristics such as axle spacing and relative axle load distributions.     

神经网络模型优化问题的研究及其应用

在研究分析多层前馈式神经网络的基础上提出了反向变量选择法，使得神经网络的高度非线性映射性能能够以尽可能少的变量实现，同时还证明了由此方法所删除的变量是对网络的输出具有最小影响的那些变量，文中还提供一个在模式识别领域的应用实例，结果令人满意。     

A NEW ESTIMATION METHOD OF SPATIAL PEAK TEMPORAL AVERAGE INTENSITY AND SPATIAL PEAK PULSE AVERAGE INTENSITY IN HIFU FIELD

High intensity focused ultrasound( HIFU) inmedicine has been developed rapidly for more thanten years.It changes the situation of slowly ad-vancing in ultrasonic therapy. HIFU has become anew character of ultrasound in medicine.The ex-tracorporal lithotriptor,the pyrothrapy,the HIFUsurgery,the HIFU hemostasis,and the HIFUabortion are the most important progresses.Theyshow that the applications of ultrasound in therapywill have greater project than that in diagnosis[1] .China has made m…     

一种新的PID参数自整定算法及其应用

本文从湖北化肥厂合成氨装置DCS系统中PID参数需手动整定的实际出发，应用系统辨识的原理，推导出一种新的HD参数自整定算法。在湖北化肥厂原DCS系统的基础上，增加一台操作站，该操作站用于下装PID参数自整定软件和基于OPC的数据接口软件，实现PID参数自整定功能。本文将这种PID自整定算法在湖北化肥厂DCS系统中进行实验，得出了HD参数自整定前后PV趋势对比图，验证了这种PID自整定算法的可行性。     

粉煤灰改善沥青混合料水稳定性后的疲劳试验研究

在沥青混合料中加入适量的粉煤灰不仅可以提高沥青混合料的水稳定性，而且还能提高沥青混合料的抗疲劳性能，这有利于提高沥青路面的使用寿命。