Parametric atmospheres: An investigation of light, material and mass as the generator for design atmosphere

<p>Parametric design today is largely embedded within a traditional trajectory. Current use largely sees the role of computers in the design studio operate at a low level, fulfilling no more sophisticated tasks than which was formerly achieved by hand. What motivation there is for parametric design tools seems to be largely inspired by a visual aesthetic. Manipulating relationships between architectural elements to design atmosphere is a long established physical process. By utilising the computer to accurately simulate spatial qualities, I propose the genesis of something more novel. The quantification of atmosphere within a digital toolset allows the designer to accurately control light, material and mass through complex networks of parametric relationships. Simulating and researching architectural atmosphere from architects Peter Zumthor and Tadao Ando allows this thesis to demonstrate a methodology for accurately simulating architectural atmosphere through the generation of geometry in Grasshopper and simulation of real site specific lighting data in 3ds Max. This thesis presents a methodology for how digital parametric design techniques enable greater flexibility and control in designing atmospheric architecture.</p>

Parametric atmospheres: An investigation of light, material and mass as the generator for design atmosphere

<p>Parametric design today is largely embedded within a traditional trajectory. Current use largely sees the role of computers in the design studio operate at a low level, fulfilling no more sophisticated tasks than which was formerly achieved by hand. What motivation there is for parametric design tools seems to be largely inspired by a visual aesthetic. Manipulating relationships between architectural elements to design atmosphere is a long established physical process. By utilising the computer to accurately simulate spatial qualities, I propose the genesis of something more novel. The quantification of atmosphere within a digital toolset allows the designer to accurately control light, material and mass through complex networks of parametric relationships. Simulating and researching architectural atmosphere from architects Peter Zumthor and Tadao Ando allows this thesis to demonstrate a methodology for accurately simulating architectural atmosphere through the generation of geometry in Grasshopper and simulation of real site specific lighting data in 3ds Max. This thesis presents a methodology for how digital parametric design techniques enable greater flexibility and control in designing atmospheric architecture.</p>

Toward Self-calibrated SM2RAIN-based rainfall product

&lt;p&gt;Reliable and detailed precipitation measurements are fundamental in many hydrological and hydraulic applications. In-situ measurements are the traditional source of this information, but the declining number of stations worldwide, the low spatial representativeness and the problems in data access, limit their relevance. In the last years, satellite products have been used to fill the gap of the ground data.&lt;/p&gt;&lt;p&gt;The estimation of precipitation by satellites can be conceptualized via two different&amp;#160; approaches: the top-down approach, where the rainfall is estimated by exploiting the electromagnetic properties of clouds, and the bottom-up approach, where rainfall is indirectly obtained by exploiting the inversion of the water balance equation once soil moisture observations are observed by satellites. SM2RAIN algorithm &lt;strong&gt;[Brocca et al., 2014]&lt;/strong&gt; belongs to the second methodology and has distinguished itself to provide accurate rainfall estimation, particularly in regions characterized by low density of rainfall gauges; however, the use of SM2RAIN relies upon a calibration dataset which represents &amp;#160;a main limitation for its applicability.&lt;/p&gt;&lt;p&gt;In this study, starting from the kwowledge of Advanced SCATterometer (ASCAT) soil moisture, topography and climatology of each pixel of land surface, a methodology for the application of SM2RAIN without using observed rainfall time series for calibration is proposed. Four parametric relationships dependent from physical descriptors of each pixel are developed by using 1009 points uniformly distributed in Australia, India, Italy and the United States, allowing the estimation of SM2RAIN parameter values- A global validation of the methodology is conducted by comparing the performance of the parametrized product against those of a calibrated SM2RAIN product. The Final Run version of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) is used for the performance assessment, together with triple collocation techniques against gauge-based Global Precipitation Climatology Center (GPCC) product and the Early Run version of IMERG.&lt;/p&gt;&lt;p&gt;The approach was also applied to a high resolution (~1 km) Soil Moisture product over test regions in Italy and Austria obtaining promising results and showing that good quality rainfall estimates at 1 km of spatial resolution can be obtained also without calibration.&lt;/p&gt;

Effects of slicing parameters on measured fill density for 3D printing of precision cylindrical constructs using Slic3r

The goal of this research is to develop and verify an algorithm to predict the fill density of 3D printed cylindrical constructs as a function of critical slicing parameters. Open-source 3D printing is being applied to the pharmaceutical and biomedical domains where characteristics including drug release rate and compressive strength depend on fill density. Understanding how slicing parameters affect fill density in the printed construct is important to appropriately tailor these characteristics. In this study, we evaluated the relationship between slicing fill density (SFD), extrusion width (EW), layer height (LH), construct diameter and measured fill density (MFD). The developed algorithm provides novel insight into the effects of interconnects and rasters on the distribution of intra-matrix material. We analyze 27 combinations involving 3 levels of EW (0.40, 0.44, 0.48 mm), SFD (15, 25, 35%) and LH (0.15, 0.20, 0.25 mm). The SFD is smaller than and deviates from MFD with a maximum error of 18.62% and from predicted fill density (PFD) with a maximum error of 19.50% compared to the maximum error of 4.30% between PFD and MFD. The predicted interconnect contribution and error reduce with increasing SFD and cylinder diameter but are more prominent at lower values. Our work highlights the perils of employing open-source 3D printing without a sound understanding of the underlying parametric relationships. The proposed predictive model could be used in conjunction with Slic3r, an open-source slicing software, to predict fill density to a reasonable degree of accuracy (less than 5% error) for relatively smaller cylindrical constructs.

Machinability Analysis of Delamination and Thrust Force in Drilling of Pure and Added GFRP Composites

The aim of this work is to define the cutting conditions that allow the drilling of added glass fiber reinforced epoxy composite materials by taking into consideration the exit delamination factor, thrust force and the optimum combination of drilling parameters. The experiments were carried out under two cutting parameters such as cutting speed and feed rate for three levels each. Taguchi experimental design is used to reduce the excessive number of experiments. The experiment design was accomplished by application of the statistical analysis of variance (ANOVA). Correlations between cutting speed/feed rate and the various machining parameters were established to optimize cutting conditions. These correlations were found by quadratic regression using response surface methodology (RSM). Multiple regression analysis (MRA) was also employed to establish parametric relationships between the experimental parameters and the machinability outputs consisting of delamination and thrust force. The machinability refers to the relative ease or difficulty under certain cutting conditions. Therefore, it is very important to understand the factors affect the machinability and to evaluate their effects. Machinability of GFRP composites was enquired. It is aimed to evaluate the machinability of these materials. A machinability index has been developed in current study.

KINEMATIC POSSIBILITIES OF "GEARED" CLOSED ROLLING BODY SYSTEMS

In technology, mechanisms are widespread that convert rotary motion into reciprocating or oscillatory. They are most often used in combination with gearboxes. Both of these functions can be performed by one mechanism - an eccentric bearing. The article discusses the problem of studying the kinematic capabilities and rational parametric relationships of various modifications of gear eccentric bearings (EPB).

DESIGN OPTIMIZATION OF A CIVIL STRUCTURE USING NUMERICAL SIMULATIONS

This optimization study aims to determine the effect of each input parameter on the output parameters, how the input parameters can interact with each other and also it is emphasized the determination of the values for the input parameters that optimize the responses. In this study, the objective is to obtain an optimal configuration for a resistance structure specific to a telecommunications tower. For this purpose, a variable geometric model using design parameters is created, based on which a 3D finite element model (FEM) is obtained, which is used in the optimization study. The FE model is updated automatically for each version of geometric model and is made using beam and shell elements. Design of Experiments (DOE) methodology allows for using a mathematical model that predicts how input parameters interact to create output responses in an optimization process. Parameters’ correlation and monitoring allow for identifying important parameters and the correlation matrix and sensitivity graphs also help understanding the parametric relationships. Variation limits for design parameters are defined and these parameters can have integer or fractional values.

Experimental Parametric Relationships for Chip Geometry in Dry Machining of the Ti6Al4V Alloy

The Ti6Al4V alloy is included in the group of difficult-to-cut materials. Segmented chips are generated for a wide range of cutting parameters. This kind of chip geometry leads to the periodic variation of machining forces, tool vibrations, and work part-tolerance inaccuracies. Therefore, the analysis of chip morphology and geometry becomes a fundamental machinability criterion. However, few studies propose experimental parametric relationships that allow predicting chip-geometry evolution as a function of cutting parameters. In this work, an experimental analysis of the influence of cutting speed and feed rate on various chip-geometric parameters in dry machining of the Ti6Al4V alloy was carried out. In addition, the chip morphology and chip microstructure were studied. A clear dependence of certain chip-geometric parameters on the cutting parameters studied was found. From the experimental data, several parametric relationships were developed. These relationships were able to predict the evolution of different geometric parameters as a function of cutting speed and feed, within the tested range of values. The differences between the proposed models and the experimental data were also highlighted. These parametric equations allowed quantifying the value of parameters in which the trend was clear.

Hard Limits and Performance Tradeoffs in a Class of Sequestration Feedback Systems

SummaryFeedback regulation is pervasive in biology at both the organismal and cellular level. In this article, we explore the properties of a particular biomolecular feedback mechanism implemented using the sequestration binding of two molecules. Our work develops an analytic framework for understanding the hard limits, performance tradeoffs, and architectural properties of this simple model of biological feedback control. Using tools from control theory, we show that there are simple parametric relationships that determine both the stability and the performance of these systems in terms of speed, robustness, steady-state error, and leakiness. These findings yield a holistic understanding of the behavior of sequestration feedback and contribute to a more general theory of biological control systems.