scholarly journals Hierarchical Design of Extraction-distillation Processes using Short-cut Apparatus Models with Piece-wise Linearized Thermodynamics

2021 ◽  
Author(s):  
Martin Kaul ◽  
Jakob Burger ◽  
Hans Hasse
Keyword(s):  
Acetic Acid ◽  
Conceptual Design ◽  
Ternary Systems ◽  
Hierarchical Optimization ◽  
Optimization Approach ◽  
Hierarchical Design ◽  
Process Stream ◽  
Robust Identification ◽  
Thermody Namics ◽  
Flowsheet Simulation

A hierarchical optimization approach for the conceptual design of extraction-distillation processes is presented. The approach includes the solvent selection and flowsheet synthesis using pinch-based short-cut apparatus models which take into account of the material balances and piece-wise linearized thermody- namics (MLT models) and is limited to ternary systems. MLT models enable fast and robust identification of feasible flowsheet-solvent combinations and op- timization thereof. Performant solvents are found by assessing process stream tables. Promising solvent-flowsheet combinations are evaluated using flowsheet simulation with detailed models, whereby the MLT results are in good agree- ment with the results of the detailed models. The approach is presented alongan example of the separation of acetic acid and water.

scholarly journals Towards an Efficient CNN Inference Architecture Enabling In-Sensor Processing

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1955
Author(s):  
Md Jubaer Hossain Pantho ◽  
Pankaj Bhowmik ◽  
Christophe Bobda
Keyword(s):  
Power Consumption ◽  
High Speed ◽  
Image Sensor ◽  
Machine Learning Algorithms ◽  
Hierarchical Optimization ◽  
Computation Method ◽  
Optimization Approach ◽  
Efficient Computation ◽  
Feature Maps ◽  
Dynamic Power

The astounding development of optical sensing imaging technology, coupled with the impressive improvements in machine learning algorithms, has increased our ability to understand and extract information from scenic events. In most cases, Convolution neural networks (CNNs) are largely adopted to infer knowledge due to their surprising success in automation, surveillance, and many other application domains. However, the convolution operations’ overwhelming computation demand has somewhat limited their use in remote sensing edge devices. In these platforms, real-time processing remains a challenging task due to the tight constraints on resources and power. Here, the transfer and processing of non-relevant image pixels act as a bottleneck on the entire system. It is possible to overcome this bottleneck by exploiting the high bandwidth available at the sensor interface by designing a CNN inference architecture near the sensor. This paper presents an attention-based pixel processing architecture to facilitate the CNN inference near the image sensor. We propose an efficient computation method to reduce the dynamic power by decreasing the overall computation of the convolution operations. The proposed method reduces redundancies by using a hierarchical optimization approach. The approach minimizes power consumption for convolution operations by exploiting the Spatio-temporal redundancies found in the incoming feature maps and performs computations only on selected regions based on their relevance score. The proposed design addresses problems related to the mapping of computations onto an array of processing elements (PEs) and introduces a suitable network structure for communication. The PEs are highly optimized to provide low latency and power for CNN applications. While designing the model, we exploit the concepts of biological vision systems to reduce computation and energy. We prototype the model in a Virtex UltraScale+ FPGA and implement it in Application Specific Integrated Circuit (ASIC) using the TSMC 90nm technology library. The results suggest that the proposed architecture significantly reduces dynamic power consumption and achieves high-speed up surpassing existing embedded processors’ computational capabilities.

System-Level Optimization Model for a Snake-Inspired Robot Based on a Rectilinear Gait

2008 ◽  
Author(s):  
James K. Hopkins ◽  
Brent W. Spranklin ◽  
Satyandra K. Gupta
Keyword(s):  
Optimization Model ◽  
Equations Of Motion ◽  
Optimal Performance ◽  
System Level ◽  
Hierarchical Optimization ◽  
Physical Parameters ◽  
Optimization Approach ◽  
Gait Parameters ◽  
Robot Performance

Physical parameters of modules and gait parameters affect the overall snake-inspired robot performance. Hence the system-level optimization model has to concurrently optimize the module parameters and the gait. The equations of motion associated with the rectilinear gait are quite complex due to the changing topology of the rectilinear gait. Embedding these equations in the system-level optimization model leads to a computationally challenging formulation. This paper presents a system-level optimization model that utilizes a hierarchical optimization approach and meta-models of the pre-computed optimal gaits to reduce the complexity of the optimization model. This approach enabled us to use an experimentally validated physics-based model of the rectilinear gait and yet at the same time enabled us to create a system-level optimization model with a manageable complexity. A detailed case study is presented to show the importance of concurrently optimizing the module parameters and the gait using our model to obtain the optimal performance for a given mission.

scholarly journals Measurement and correlation of interfacial tensions for water-hydrocarbon-acetic acid ternary systems.

1989 ◽  
Vol 15 (5) ◽  
pp. 1026-1030 ◽  
Author(s):  
Shunsuke Nakahara ◽  
Hiroshi Masamoto ◽  
Yasuhiko Arai
Keyword(s):  
Acetic Acid ◽  
Ternary Systems ◽  
Interfacial Tensions

Conceptual Design and Prototype Development of a Solar-Powered Ground Robot for Energy-Autonomous Operation

2019 ◽  
Author(s):  
Amir Behjat ◽  
Leighton Collins ◽  
Andrew Hoffman ◽  
Sharat Chidambaran ◽  
Maulikkumar Dhameliya ◽  
...  
Keyword(s):  
Conceptual Design ◽  
Incident Angle ◽  
Optimization Approach ◽  
Solar Pv ◽  
Solar Panels ◽  
Energy Capture ◽  
Prototype Development ◽  
Autonomous Operation ◽  
Outdoor Environments ◽  
Solar Powered

Abstract This paper presents the conceptual design and fabrication/assembly of an autonomous solar powered small unmanned ground vehicle (UGV) platform for operation in outdoor environments. The contribution lies in the ability of the proposed design to offer uninterrupted operation in terms of endurance, to facilitate educational and research applications that are otherwise challenging to perform with a typical UGV (that needs significant downtime for recharging). A high incident area for solar PV panels is required to be able to support the complete energy needs of a ∼ 46 lb UGV (i.e., fully recharge the suitably sized battery powering the UGV). This makes it challenging to develop a stable platform that can carry solar panels much larger than the surface area of the platform itself (an aspect receiving minimal attention in other similar purpose platforms). To address this challenge, a novel umbrella-like folding mechanism is conceived, designed and successfully incorporated in the baseline prototype. This mechanism allows incorporating a remarkable ∼1 sq.m of incident solar PV with a net rated capacity of 200 W, one that remains folded to facilitate mobility, and can open/unfold to different extents for energy capture when needed. At the same time, the proposed design facilitates static and dynamic stability in spite of the significant solar PV incorporation. With the reference of the baseline prototype, an optimization approach is taken to develop a conceptual design of the next generation of this solar UGV. Specifically, the incident angle of the solar panels (enabled by the umbrella mechanism) at complete-open stage and the dimensions of the mechanism links and associated supports are separately optimized to respectively maximize the energy capture and the range of the UGV (assuming operation in Buffalo, NY), subject to stability and nominal velocity (of 2km/hr) constraints. The optimum design is found to provide an estimated range of 19.8 km/day.

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