Cooling Intensity of Inverse Solubility Polyalkylene Glykol Polymers and Some Results of Investigations Focused on Minimizing Distortion of Metal Components

Poly(Alkylene Glycol) polymers of inverse solubility (PAG) provide ideal uniform cooling for minimizing distortion and preventing crack formation during hardening machine components and tools. However, in spite of ideal cooling, from time to time, a big distortion takes place during hardening process. A reason for a big distortion development during hardening in PAG solutions is explained and an idea how to fix the problem is suggested. It is shown that at the end of cooling coating can be locally dissolved by a cold water flow creating local open area where martensite transformation starts first. Due to greater specific volume of martensite, it creates a big distortion. To solve the problem, one should interrupt cooling process or stop agitation before insulating coating is dissolved. To perform correctly proposed technology, cooling intensity of inverse solubility PAG polymers of 1–20 % were investigated on the basis of use of regular thermal condition theory. As a result, dimensionless effective numbers Kn were obtained for recipes development. A technique for solving the problem is proposed by author. Examples of calculations are provided

Automating embedded analysis capabilities and managing software complexity in multiphysics simulation part II: application to partial differential equations

A template-based generic programming approach was presented in a previous paper that separates the development effort of programming a physical model from that of computing additional quantities, such as derivatives, needed for embedded analysis algorithms. In this paper, we describe the implementation details for using the template-based generic programming approach for simulation and analysis of partial differential equations (PDEs). We detail several of the hurdles that we have encountered, and some of the software infrastructure developed to overcome them. We end with a demonstration where we present shape optimization and uncertainty quantification results for a 3D PDE application

Deep geothermal exploration by means of electromagnetic methods: New insights from the Larderello geothermal field (Italy)

The main target of this research is the improvement of the knowledge on the deep structures of the Larderello-Travale geothermal field (Tuscany, Italy), with a focus on the Lago Boracifero sector, particularly on the heat source of the system, the tectonics and its relation with the hydrothermal circulation. In the frame of the PhD program and of the IMAGE project (Integrated Methods for Advanced Geothermal Exploration; EU FP7), we acquired new magnetotelluric (MT) and Time Domain EM (TDEM) data in a key sector of the field (Lago Boracifero). These data integrate the MT datasets previously acquired in the frame of exploration and scientific projects. This study is based also on a integrated modelling, which included and organized in Petrel (Schlumberger) environment, a large quantity of geological and geophysical data. We also propose an integrated approach to improve the reliability of the 2D MT inversion models, by using external information from the integrated model of the field as well as an innovative probabilistic analysis of the MT data. We present our attempt to treat the 1D magnetotelluric inverse problem with a probabilistic approach, by adopting the Particle Swarm Optimization (PSO), a heuristic method based on the concept of the adaptive behaviour to solve complex problems. The user-friendly software “GlobalEM” was implemented for the analysis and probabilistic optimization of MT data. The results from theoretical and measured MT data are promising, also for the possibility to implement different schemes of constrained optimization as well as joint optimization (e.g. MT and TDEM). The analysis of the a-posteriori distribution of the results can be of help to understand the reliability of the model. The 2D MT inversion models and the integrated study of the Larderello-Travale geothermal field improved the knowledge about the deep structures of the system, with a relevant impact on the conceptual geothermal model. In Micaschist and Gneiss complexes we observed a generally high electrical resistivity response locally interrupted by low resistivity anomalies that are well correlated with the most productive sectors of the field. A still partial melted igneous intrusion beneath the Lago Boracifero sector was detected based on the interpretation of the low resistivity anomalies located at a mid-crustal level (> 6 km). New insights on the tectonics are proposed in this research. The fundamental role of a large tectonic structure, i.e. the Cornia Fault, located along the homonymous river, was highlighted. In our opinion, this fault played an important role in the geothermal evolution of the Lago Boracifero sector, favouring both the hydrothermal circulation and the emplacement of magma bodies. In our opinion, the system can be ascribed to a “young convective and intrusive” field feed by a complex composite batholite

Asteroid Models from Multiple Data Sources

In the past decade, hundreds of asteroid shape models have been derived using the lightcurve inversion method. At the same time, a new framework of 3-D shape modeling based on the combined analysis of widely different data sources such as optical lightcurves, disk-resolved images, stellar occultation timings, mid-infrared thermal radiometry, optical interferometry, and radar delay-Doppler data, has been developed. This multi-data approach allows the determination of most of the physical and surface properties of asteroids in a single, coherent inversion, with spectacular results. We review the main results of asteroid lightcurve inversion and also recent advances in multi-data modeling. We show that models based on remote sensing data were confirmed by spacecraft encounters with asteroids, and we discuss how the multiplication of highly detailed 3-D models will help to refine our general knowledge of the asteroid population. The physical and surface properties of asteroids, i.e., their spin, 3-D shape, density, thermal inertia, surface roughness, are among the least known of all asteroid properties. Apart for the albedo and diameter, we have access to the whole picture for only a few hundreds of asteroids. These quantities are nevertheless very important to understand as they affect the non-gravitational Yarkovsky effect responsible for meteorite delivery to Earth, or the bulk composition and internal structure of asteroids.Comment: chapter that will appear in a Space Science Series book Asteroids I

Comparisons of Ablator Experimental Performance to Response Modeling and Effects of Water Phase Transition in Porous TPS Materials

The Mars Science Laboratory Entry Descent and Landing Instrumentation (MEDLI) project performed extensive arc jet tests for development, qualification, and calibration of instrumented heat shield plugs. These plugs each contained several thermocouples for recording near-surface and in-depth temperature response of the Phenolic Impregnated Carbon Ablator (PICA) heat shield. The arc jet test results are entered into a comprehensive database so that broad trends across the test series can be compared. One method of analysis is to compare with ablator material response calculations and solve the in-depth heat conduction equations. Using the near-surface thermocouple measurements as a boundary condition in numerical simulations, comparisons are made with other thermocouple measurements taken deeper within the TPS test article. The work presented here uses this technique to compare test results with model simulations using several metrics, such as peak-temperature difference, maximum difference in temperature, and a total integrated temperature deviation. A significant difference in prediction behavior with respect to the location of source thermocouple is shown based on these comparisons. The temperature prediction accuracy is quantified for the tested material and material response code and is found to be highly dependent on the distance between the boundary condition thermocouple and the deeper reference thermocouple. Based on this test data, it is shown that numerical models can predict in-depth temperature measurements equally well for sensor plugs installed in the arc jet test model with or without a silicone adhesive. It is found that predicted temperatures are consistently greater than measured values, indicating the PICA material model is generally conservative for in-depth temperature predictions. In addition, a low-temperature phenomenon was consistently observed through thermocouple measurements deep within the material during the MEDLI arc jet testing. This anomaly, referred to here as the hump, consists of a change in concavity of the temperature profile well below the maximum temperature and is seen in various TPS materials and atmospheric conditions, and typically occurs around 40 ºC. It is proposed that the observed ``hump is a result of the heat of vaporization during the endothermic phase transition of water within the TPS material. This is supported by the known absorption of water by PICA from the atmosphere prior to testing or flight. The presented material response model captures energy effects of phase transition from a pre-existing water presence. This work shows that water presence currently appears to be the most probable cause for the phenomenon, which is observed in multiple different porous TPS materials

Development of thin surface virtual sensors for predictive maintenance

Mestrado de dupla diplomação com a UTFPR, Universidade Tecnológica Federal do ParanáIn the field of manufacturing, metal stamping and plastic injection are some essential procedures, such that companies in this sector need to optimize these processes to gain a competitive advantage. In this sense, this work is part of the On-Surf project, which aims to develop surface modification processes, which promote advanced solutions within the transformation industry through surface engineering techniques. This work proposes the study of techniques based on virtual sensors, to monitor the temperature of a plastic injection mold in real time. The method makes use of Computer Aided Engineering (CAE) software to model the injection system, mathematical software to adjust the process equations, and an algorithm developed in Python that calculates the value of the soft sensors from the input of one or multiple physical sensors. The work makes use of case studies of simple metallic surfaces to define the thermal behavior and associate it with a correlation factor. Then apply the techniques developed in the geometry of an injection mold. Through the use of soft sensors, it is possible to obtain more temperature points about the mold. Such information is extremely important for the predictive maintenance (PdM) of the machine, since it aims to facilitate the operational parameters decision making, reducing the probability of failures, both in the manufactured parts and in the physical sensors themselves, because the technique guarantees the monitoring of the values in real time.Na área de manufatura, estampagem e injeção de plástico são alguns procedimentos essenciais, de forma que as empresas do setor precisam otimizar esses processos para ganhar vantagem competitiva. Neste sentido, este trabalho é parte do projeto On-Surf, que visa desenvolver soluções avançadas dentro da indústria de transformação através de técnicas de engenharia de superfícies. Este trabalho propõe o desenvolvimento de sensores virtuais, para monitorar a tem- peratura de um molde de injeção de plástico em tempo real. O método utiliza um software de Engenharia Assistida por Computador (CAE) para modelar o sistema de injeção, um software matemático para ajustar as equações do processo e um algoritmo desenvolvido em Python que infere o valor dos sensores virtuais a partir da entrada de um ou vários sensores físicos. O trabalho faz uso de estudos de caso de superfícies metálicas simples para definir o comportamento termico e associar a um fator de correlação. A seguir aplicam-se essas técnicas desenvolvidas na geometria de um molde de injeção. Com o uso de sensores virtuais, será possível obter mais pontos de temperatura sobre o molde. Tais informações são extremamente importantes para a manutenção preditiva (PdM) da máquina, pois facilita a tomada de decisão dos parâmetros operacionais, re- duzindo a probabilidade de falhas, tanto nas peças fabricadas quanto nos próprios sensores físicos, devido o monitoramento dos valores em tempo real

Champs-Multizone and Virtual Building for Integrated Building Systems Design and Performance Evaluation

The ultimate goal of this research was to develop an integrated framework that facilitates performance-based multi-stage design of buildings and comparison between the performance predicted at the design stage and that monitored at operation stage. Such an integrated framework would not only enable design optimization, but also enable confirmation of design intent or diagnosis of performance deficiency, and thus provide feedbacks for future building design. This dissertation study represents the first step toward this ultimate goal, and had the following specific objectives:: 1) developing a combined heat, air, moisture and pollutant transport model for whole building performance simulation; 2) developing a real-time building IEQ and energy performance monitoring system using a Virtual Building structure to facilitate fast comparison between design and montored performance.; 3) developing a methodology to use CHAMPS-Multizone for a green building design throughout its initial and final design stage. The CHAMPS-Multizone model consists of building envelope model, room model, HVAC model and airflow model, and has an efficient and accurate numeric solvers. The model is tested under different building cases including ASHRAE 140 standard test and a three zones building test and comparision with EnergyPlus calculation results. The Virtual Building is a digital representation of the physical building with a hierarchical data structure, containing both static data such as enclosure assemblies, internal layout, etc. and dynamic data such as occupant activity schedule, outdoor weather conditions, indoor environmental parameters, HVAC operation data and energy consumption data. Then, the Virtual Building approach has been demonstrated in a LEED office building with its monitoring system. Finally, a multi-stage design process was formulated that considers the impact of climate and site, form and massing, external enclosure, internal configuration and environmental system on the whole building performance as simulated by CHAMPS-Multizone. Using the testbed building, both simulation results were also compared with the results monitored by the Virtual Building monitoring system. Future research includes refining CHAMPS-Multizone simulation capability and adding modules such as water loop calculation and integrating HVAC calculation with EnergyPlus

Experimental Testing of a Computer Aided Heat Treatment Planning System

Heat treatment is an important manufacturing process, which controls the mechanical property of metal parts, therefore contributes to the product quality. A Computerized Heat Treatment (CHT) system has been developed to model and simulate the heat transfer in furnace. When the part load and thermal schedule information is given with part and furnace specifications, the temperature profiles of parts in furnace can be calculated based on heat transfer principle. Therefore the part load and thermal schedule can be optimized to remove unnecessary delay time while the quality of heat treatment is ensured. In the thesis, the functions of CHT are enhanced with the capability of modeling and simulating the heat treatment processes with random part load and continuous furnaces. Methods to model random load and continuous furnace have been developed. Case studies with industry real data have been conducted to validate the system and to show effectiveness of the system. The system development is also introduced in the thesis