In the previous post, we have discussed about how interpolation works in general and reviewed a few commonly used interpolation methods. All these methods only consider the adjacent a few points. This works fine most of the time. However, in reality, data points further away from the interpolation point may also have some impact on…
Workflows is d3VIEW’s application for streamlining complex business processes. With its capabilities, we can create and employ automated DOE studies for quicker analysis. Using the application’s new shape worker, *TEXT_PARAMETERIZE_GUI, we can set-up custom parameters for our text-based files, generate sampling points from these parameters, create simulations from the text, launch the DOE studies from…
d3VIEW’s visualization application Simlytiks® now has a new page layout called Dashboard that allows users to set-up a free-form presentation-styled page using dedicated widgets. Add custom text, images, data filters and aggregators, and Simlytiks charts as well. To better illustrate Simlytiks Dashboard capabilities, we’ll be looking at the Iris Class dataset which looks at how…
d3VIEW supports material calibration and storage of calibrated materials in a scientific database native to d3VIEW. Once materials are stored in the database, d3VIEW supports filters to search and retrieve the materials of choice. Recently, we have been working on supporting visual selection through “Brushing” – a term often used to describe the ability to…
Introduction Given a set of points, we want to construct a curve that shares some specific patterns described by a group of curves. From the description of the problem, there are two pieces of information available to us. First, the points available (Prediction Points) are part of an unknown curve we want to reconstruct. Second,…
Machine learning is a data analysis technique that builds a model with the data and uses the model to predict. It learns from the data, identifies patterns and produces reliable predictions that help with decision making. As modern computational techniques advance, machine learning becomes more and more popular. There are two major groups of learning…
It is not unusual that due to various limitations, researchers can only collect limited number of samples. Meanwhile, for many analyses, we desire a higher resolution. In two-dimension case, we have X and Y coordinates of our points. We are interested in what happens in between any of the two points. We can draw a…
There is no excerpt because this is a protected post.
Battery data have many interesting properties. One of them is cycles. When we consider the whole range of the data, there are a few of the metrics we are interested in. For example, test net capacity and energy, test cumulative capacity and energy, etc. From these transformed curves, we can obtain some metrics that help…
As simulations drive a large portion of product development, reliance on test-data at critical development stages is invaluable to further our understanding of reality and assess our simulations. Among a wide variety of tests conducted today, the test-data can be broadly grouped into coupon-based (for material calibration), component based (for sub-system validation) and full-system tests.…
