A Compact Representation of Measured BRDFs Using Neural Processes

In this article, we introduce a compact representation for measured BRDFs by leveraging Neural Processes (NPs). Unlike prior methods that express those BRDFs as discrete high-dimensional matrices or tensors, our technique considers measured BRDFs as continuous functions and works in corresponding function spaces . Specifically, provided the evaluations of a set of BRDFs, such as ones in MERL and EPFL datasets, our method learns a low-dimensional latent space as well as a few neural networks to encode and decode these measured BRDFs or new BRDFs into and from this space in a non-linear fashion. Leveraging this latent space and the flexibility offered by the NPs formulation, our encoded BRDFs are highly compact and offer a level of accuracy better than prior methods. We demonstrate the practical usefulness of our approach via two important applications, BRDF compression and editing. Additionally, we design two alternative post-trained decoders to, respectively, achieve better compression ratio for individual BRDFs and enable importance sampling of BRDFs.

Research on Key Factors of Sealing Performance of Combined Sealing Ring

In this study, the mechanical properties of a combined seal ring under different loads were numerically calculated using ANSYS. The effect of the working pressure and pre-compression ratio of a rubber O-ring on the contact stress of the combined seal ring was studied. The influence of the wear ring’s chamfer, thickness, and width on the contact stress and contact force of the combined seal ring was analyzed. Studies have shown that it is particularly important to select a compression ratio that is suitable for the working conditions. Under the same conditions of working pressure and compression ratio, upon increasing the wear ring chamfer, the contact pressure is decreased due to the decreasing contact bandwidth between the wear ring and the cylinder wall. This has little effect on the contact stress of the combined seal ring as well as the contact force, while the width of the wear ring is proportional to the latter.

OPTIMIZATION OF METHODS AND PARAMETERS OF PRE-START THERMAL PREPARATION OF THE ENGINE FOR STARTING DEPENDING ON THE AMBIENT TEMPERATURE

Due to the lack of a generally accepted methodology for calculating the starting processes of automotive diesel engines, today it is not possible to calculate their temperature parameters with a sufficient degree of accuracy during start-up, which determine the condition of a guaranteed start-up process. The main problem in applying theoretical calculations is that they take into account the compression ratio of the engine. But the compression ratio and the value of the actual pressure in the engine cylinders during the start-up are completely different indicators. The purpose of this work is to correct the generally accepted dependencies for determining the temperature parameters of a diesel engine by introducing a correction factor that takes into account the reduced pressure in the engine cylinders during start-up, as well as calculating the temperature parameters during start-up according to the proposed calculation method. The correction factor is determined experimentally and depends on the engine temperature. When applying the correction factor, it becomes possible to accurately calculate the temperature of the fuel-air mixture, which determines the possibility of a guaranteed start-up process and at the same time allows you to set the minimum necessary requirements for the means of thermal pre-start preparation. A group of graduate students and teachers (Izhevsk State Agricultural Academy and Kazan Agrarian University) conducted a number of practical studies on the basis of one of the leading agricultural enterprises of the Udmurt Republic JSC "Ilyich's Way". The MTZ-82 tractor was taken as the object of the study. The subject of the study was the launch of its D-243 engine at low temperatures in real operating conditions. The choice of this model of diesel engine is due to its wide application on tractors. The studies were carried out according to the approved test program, which consists in starting the D-243 engine of the MTZ-82 tractor at temperatures from - 30 ° C with an interval of 5 ° C to +5 ° C (engine temperature is equal to ambient temperature), as well as from +5 ° C to +90 ° C with an interval of 20 ° C (ambient temperature +20 ° C). Measurements were carried out to determine the amount of compression in the engine cylinders and the speed of rotation of the crankshaft at certain temperatures. The experiments were carried out using a starter charger that provides the full electric power of the diesel starter. As a result of the experimental work carried out, a change in the value of the correction coefficient from the engine temperature was established, and in accordance with the modified methodology of theoretical calculations, the values of the temperature of the fuel-air mixture at the end of the compression stroke of the diesel engine at start-up are given. It is established that the minimum required pre-start temperature of the diesel engine should be at least +5 ° C. Based on the results of the analysis of calculations, the directions of ensuring a guaranteed start of the diesel engine by simultaneously heating the coolant and engine oil are proposed. These requirements can be provided by a thermal storage system that does not require additional energy sources for its operation

Principle and structure of a multi-chamber piezoelectric pump with large flow rate integrated into printed circuit board

Parametric simulation of multi-chamber piezoelectric pump proposed by authors shows that its flow rate is positively correlated with chamber compression ratio when height of chamber wall is not less than central deflection of circular piezoelectric unimorph actuator (CPUA). Therefore, in this paper, principle and structure of multi-chamber piezoelectric pump with novel CPUAs with three-layer structure are proposed and realized, so as to improve its chamber compression ratio, and then improve its flow rate. Its processing technology compatible with PCB processing technology is studied and its flow rate model is established. Central deflection of CPUA with three-layer structure and the flow rate characteristics are tested. Experimental results show that when the central deflection of CPUA with three-layer structure reaches the maximum value of 106.8 μm, the chamber compression ratio and flow rate of multi-chamber piezoelectric pump reach the maximum value of 50% and 3.11 mL/min, respectively. The maximum flow rate is increased by 622% compared to unimproved pump. By comparing experimental results with numerical and finite element simulation results, the realized multi-chamber piezoelectric pump has large flow rate and the established flow rate model can predict its flow rate.

Compression and Decompression which Use Deep Neural Network

<p>an auto-encoder which can be split into two parts is designed. The two parts can work well separately. The top half is an abstract network which is trained by supervised learning and can be used to classify and regress. The bottom half is a concrete network which is accomplished by inverse function and trained by self-supervised learning. It can generate the input of abstract network from concept or label. It is tested by tensorflow and mnist dataset. The abstract network is like LeNet-5. The concrete network is the inverse of the abstract network.Lossy compression can achieved by the test. The large compression ratio which is 19.6 is achieved. The decompression performance is ok through regression which treats classification as regression.</p>