A diesel engine air path model with a WG and an ETV for exhaust temperature controller design and embedded control

In this paper a mean value model of a turbocharged diesel engine air path with an electric wastegate (WG) and an exhaust throttle valve (ETV) is presented. The model is designed with regard to system analysis, controller design, and real-time feasibility. That means, care is taken to ensure that the model contains the relevant dynamics on the one hand and that the requirements for computing power and memory (RAM) are kept as low as possible on the other hand. New approaches for modeling the ETV and the exhaust gas temperature are presented. The latter is formulated via an artificial neural network (ANN) computed outside the model. The ANN is integrated into the model in such a way that the differentiation of the model still provides meaningful results for controller design. Thus, this model may also be used for online computation of nonlinear model predictive controllers (MPC) or nonlinear state observers. The parameters of the model are determined using GT-Power simulation data covering the entire working range of the engine. Only measured variables that are also accessible on the engine test bench are used. All optimization problems to be solved within the parameter determination are presented. It is analyzed which sensors are suitable to support the model in an implementation on an electronic control unit (ECU), and the effect without and with sensor correction is shown in a dynamic test bench measurement. Furthermore, the properties of the generated C code are presented, which are the number of mathematical operations, the runtimes, and the stack size. An evaluation of the real time capability is given based on eigenvalue analyses and the properties of the C code .

Efficient 2D multiple attenuation using SRME with curvelet-domain subtraction

Surface Related Multiple Elimination (SRME) usually suffers the issue of either over-attenuation that damages the primaries or under-attenuation that leaves strong residual multiples. This dilemma happens commonly when SRME is combined with least-squares subtraction. Here we introduce a more sophisticated subtraction approach that facilitates better separation of multiples from primaries. Curvelet-domain subtraction transforms both the data and the multiple model into the curvelet domain, where different frequency bands (scales) and event directions (orientations) are represented by a finite number of curvelet coefficients. When combined with adaptive subtraction in the time–space domain, this method can handle model prediction errors to achieve effective subtraction. We demonstrate this method on two 2D surveys from the TAiwan Integrated GEodynamics Research (TAIGER) project. With a careful parameter determination flow, our result shows curvelet-domain subtraction outperforms least-squares subtraction in all geological settings. We also present one failed case where specific geological condition hinders proper multiple subtraction. We further demonstrate that even for data acquired with short cables, curvelet-domain subtraction can still provide better results than least-squares subtraction. We recommend this method as the standard processing flow for multi-channel seismic data.

Route Optimization via Environment-Aware Deep Network and Reinforcement Learning

Vehicle mobility optimization in urban areas is a long-standing problem in smart city and spatial data analysis. Given the complex urban scenario and unpredictable social events, our work focuses on developing a mobile sequential recommendation system to maximize the profitability of vehicle service providers (e.g., taxi drivers). In particular, we treat the dynamic route optimization problem as a long-term sequential decision-making task. A reinforcement-learning framework is proposed to tackle this problem, by integrating a self-check mechanism and a deep neural network for customer pick-up point monitoring. To account for unexpected situations (e.g., the COVID-19 outbreak), our method is designed to be capable of handling related environment changes with a self-adaptive parameter determination mechanism. Based on the yellow taxi data in New York City and vicinity before and after the COVID-19 outbreak, we have conducted comprehensive experiments to evaluate the effectiveness of our method. The results show consistently excellent performance, from hourly to weekly measures, to support the superiority of our method over the state-of-the-art methods (i.e., with more than 98% improvement in terms of the profitability for taxi drivers).

Substantion of the energy approach to parameter determination of the cyclic ice force against offshore structures

Определение величины силового воздействия ледовых образований на морское ледостойкое основание производится по расчетной формуле, описывающей принятую модель разрушения льда. Лед в контактной зоне ледового поля с сооружением, в зависимости от его температуры и скорости взаимодействия, может разрушаться в широком диапазоне механизмов его разрушения – от вязкого до хрупкого. Здесь представлена разработка модели упруго-хрупкого разрушения льда, учитывающая разрушение кромки ледового поля всеми возможными типами трещин, делящими локальную область массива льда в зоне контакта с сооружением на клиновидные или трапециевидные фрагменты. Предложено все процессы разрушения льда, имеющие различную природу, рассматривать как единообразный, но комплексный процесс, математическое описание которого во времени можно выполнить с использованием универсального энергетического критерия разрушения. Приводятся обоснования закономерности такого подхода, основанные на феноменологическом анализе явления циклического разрушения льда в контактной зоне, на результатах численного моделирования картины развития разрушений в массиве льда у кромки ледовой плиты на контакте с опорой сооружения, а также на данных физического моделирования изучаемого процесса. В качестве универсального критерия в работе рассматривается предельное значение накопленной в единице объема льда перед сооружением потенциальной энергии упругого сжатия – удельной упругой энергии механического разрушения морского льда.

Repair Performance Landslide and Slope Using Bore pile and Ground Anchor on Cipali Toll Road Km 103

One of the causes of on-road collapse slopes is traffic load. Slope failure by road loads usually occurs due to several factors such as soil type, rainfall, land use. This study aims to determine landslide and slope repair performance using bore pile and ground anchor on Cipali Toll Road KM 103. The research method used in this study is the Finite element method. In this research, data collection, modeling parameter determination, slope stability analysis, slope reinforcement analysis, and reinforcement design were carried out with variations in bore pile and ground anchor dimensions. The software program used is a finite element program in the form of PLAXIS to analyze slope stability and estimate the slope failure area. The result of the study is that the R-Value inter is 0.25 with a 1.0341 safety factor. Best repair performance obtained from the addition of reinforcement with ground anchor 2 layer on bore pile 2 with a distance of 2 meters increased the safety factor to 1,913; Borepile capacity calculation with the calculation of normal force and moment iteration, the largest occurs in the DPT (Retaining Wall) stage with a normal load of -37.9 and a moment force of -471.15 which is still able to be borne by bore pile 1. The result of this study is expected to be benchmark and repair material to improve slope stability at km 103 Tol Cipali

Hyperelastic Material Parameter Determination and Numerical Study of TPU and PDMS Dampers

Dampers provide safety by controlling unwanted motion that is caused due to the conversion of mechanical work into another form of energy (e.g., heat). State-of-the-art materials are elastomers and include thermoplastic elastomers. For the polymer-appropriate replacement of multi-component shock absorbers comprising mounts, rods, hydraulic fluids, pneumatic devices, or electro-magnetic devices, among others, in-depth insights into the mechanical characteristics of damper materials are required. The ultimate objective is to reduce complexity by utilizing inherent material damping rather than structural (multi-component) damping properties. The objective of this work was to compare the damping behavior of different elastomeric materials including thermoplastic poly(urethane) (TPU) and silicone rubber blends (mixtures of different poly(dimethylsiloxane) (PDMS)). Therefore, the materials were hyper- and viscoelastic characterized, a finite element calculation of a ball drop test was performed, and for validation, the rebound resilience was measured experimentally. The results revealed that the material parameter determination methodology is reliable, and the data that were applied for simulation led to realistic predictions. Interestingly, the rebound resilience of the mixture of soft and hard PDMS (50:50) wt% was the highest, and the lowest values were measured for TPU.