Solid modelling project complete the overall design and the design of the various vice components from the diagrams provided. More specifically you are required to: 1. Create parametric feature-based solid models for all the components either shown or listed in the following pages. This includes the rubber jaw protectors. 2. Create an assembly model showing all parts in their working position when the opposing faces of the hard jaws are separated by 30 mm and when the ball to screw distance is set at 55mm. 3. Set up a parametric relationship equation between the Base and the Clamp to satisfy the design requirement as outlined in the Background information above. 2 MEC2304 – Solid modelling 4. Produce an engineering assembly drawing of the vice as configured in 2 above. In addition to the orthographic views the drawing should also include a 3D view, title block, parts lists, and other information generally shown in assembly drawings. 5. Produce fully dimensioned engineering detail drawings for the parts listed below: • Base • Swivel jaw • Sliding jaw • Clamp • Guides and bushes • Rubber pad with the metal lug • Jaw inserts and jaw-face protectors Specify appropriate surface finish requirements, general tolerances, and other information normally shown in a detail drawing. Also include a 3D view of the part in addition to the orthographic views or view. 6. Nominate and justify suitable fits and tolerances on a separate A4 sheet for the following mating parts / features: • Bush / jaw bush hole / guide pin The basic size and tolerance sizes for each fit should be included on the sheet. The tolerance sizes should also appear in the detail drawings. Guidance on the Project The diagrams provided show limited details and in many cases the dimensioning of the details
I need model of wind turbine using PMSG , more details in PMP
I would like to have a CFD analysis for a mini-municipal solid waste pyrolysis reactor. I have a model. You only will make an analysis. I do not know how to use FLUENT very well. I have some datas about it. But I dont know which is necessary for analysis. So you can ask me what is necessary for it. temperature, pressure, velocity etc.
design and analysis different springs and find the [url removed, login to view] of the numerical analysis.
I am looking for someone with experience with "Arena Simulation" tool: [url removed, login to view] In the scope of this project I need to create a basic simple model with 5 components. In follow up projects (or milestones) I will wish to extend the basic model.
I need someone use IH2VOF (link: [url removed, login to view]) to analysis Overtopping wave capacity for sea dyke
I would like a model of a surfboard created (the surfboard shape will be a replica of a real board I manufacture). Followed by CFD testing at multiple angles to determine the water flow, pressure and resistance. I will require the data in images and also a video file showing the product partially submerged in water doing a gradual turn (up to 90 degrees). I can provide you with model dimensions and further details once successful
I am looking for TOS script for the below requirements: Price Range : $2 to $50 Volume : Minimum - 400,000 Moving Average: Exp - 8 Moving Average Exp - 34 VWAP It should work in any time frame , values should be able to adjust When Moving Avg (8) is above Moving Avg (34) and crossing above VWAP within one or two bars. Also it should be a strategy for Auto trading (option to enable/disable)
we will consider use of PCA for simple dimensionality reduction, i.e., determining the signal subspace when there are more observations than the underlying latent variables—signals. The main assumption here is that both the noise and signals are independent and identically distributed Gaussians, however the the signals are correlated among themselves while the noise components are not, they are all uncorrelated—and hence independent as well. Assume there are five signal components and five noise components, and generate 1000 samples of each. You can use knee point detection function available in Matlab [url removed, login to view] fileexchange/35094-knee-point to determine the order of signal subspace, i.e., number of signal components. Generate two different correlation profiles for signals such that for one of those knee point detection will work well but will not be able to determine the true order of five for the second case. Make sure that all signal and noise components have the same variance, which is unit variance.
The goal of this project is to construct a spreadsheet model that will allow an analyst to predict the graduation rate of a college or university depending upon several factors: • Whether the institution is a liberal arts college or university; • Median SAT score of students at the institution; • Acceptance rate of the college or university; • Expenditures per student; • Percentage of students in the top 10% of their high school class. Part 1: Perform regression analysis by constructing a model to predict the graduation rate of a college or university. Complete the following steps: a. Assess the data using descriptive statistics. Include various descriptive measures (mean, max, mode, median, min, standard deviation, etc.) Use histograms, if appropriate, and analyze any outliers you find in the data. Record what you learn. b. Plot the data. Analyze and record what you learn from the various scatter plots. c. Determine the correlation between the dependent variable and the various independent variables by creating a correlation matrix. Assess for multicollinearity between the independent variables. d. Assess the predictive capability of this data using both simple and multiple linear regression, including the use of a dummy (categorical independent) variable of whether the student attended a college or university. Run the regressions, perform statistical inference in each case, and record what you learn. Use a 0.05 level of significance. If you assess that there is not a relationship between any two variables of data, redo the regression equation and assessments showing only the data points with linear relationships. If you find multicollinearity, remove it by redoing your model without one of the variables causing multicollinearity, then try it with the other variable removed and pick the best option. e. Based on the prior steps, determine and record the best linear regression equation for this data. Discuss the meaning of the model fit and regression coefficients. f. Assess the possibility of a better curvilinear regression line. If your findings warrant this, run the curvilinear regression and discuss the meaning of the model fit and the regression coefficients. g. Pick the best regression equation and document it. h. Using your best regression equation, what is your graduation rate prediction for a university whose student median SAT score is 1210, acceptance rate is 23%, expenditures per student are $25,500, and the percentage of students in the top ten percent of their graduating HS class is 79%? i. Remove any extreme outliers in the data and rerun the regression analysis. Is your best model after completing this step better? j. What other independent variables (not cited in the data) may be important in improving this model?
There is a service class called PurchaseOrder that is called when a customer makes a purchase. It has a public method purchase(Account, Order). It does the following. a. Call [url removed, login to view]() b. Call [url removed, login to view](Account) c. Call [url removed, login to view]() d. [url removed, login to view]() calls [url removed, login to view](amount) which makes the payment e. Call [url removed, login to view](Order) which saves the order f. Call [url removed, login to view]() which commits the order g. Call [url removed, login to view](order) which logs that an order has been placed I want to write a sequence diagram showing how the methods are called.
project should contain information on passive solar technologies
Design, Ansys analysis, report