A physical property estimation device for a resin composition, which estimates a physical property of a resin composition that is manufactured by using a base polymer, a flame retardant, a flame retardant auxiliary, and other materials. The physical property estimation device is provided with a regression model building processing unit that learns by machine learning a relationship between explanatory variable data and physical property data including physical property data as an estimation target, and builds a regression model that shows a correlation between the explanatory variable data and the physical property data, and a physical property estimation processing unit that estimates the physical property of an estimation target by using the regression model. The explanatory variable data includes compound amount data of the base polymer, the flame retardant, and the flame retardant auxiliary respectively, when a physical property to be estimated by the physical property estimation processing unit is either initial elongation or initial tensile strength of the estimation target.

A non-transitory computer readable storage medium with a destruction prediction program causing a computer to determine destruction prediction of a resin molding, and to function as a first calculation portion that calculates a maximum value of an equivalent strain that occurs in a cutout bottom and an inclination of an equivalent strain by applying, to a 3D test piece model of a test piece, a load at breaking the test piece, a threshold set portion that sets a threshold E of destruction progress based on the maximum value and the inclination, a second calculation portion that calculates a maximum value of an occurring equivalent strain and an inclination of an equivalent strain by applying a load to the 3D target model, and a destruction determination portion that determines whether or not destruction occurs based on the maximum value and the inclination, and the threshold.

Provided is an analysis apparatus configured to analyze characteristics of a viscoelastic material based on a viscoelastic material constitutive law in which an elastic element and a viscoelastic element are arranged in parallel with each other; calculate, in a viscoelastic material model divided into a finite number of elements each having a node, a displacement amount of the node; calculate a strain rate at the node through use of the displacement amount; calculate, as a relaxation time of the viscoelastic element, a value proportional to a value of a power using the strain rate as a base and a value of a power using a shift factor of a temperature-time conversion law as a base; and calculate a stress at the node through use of the relaxation time.

This is an approach to the prediction of soil density and subsoil crop growth. The approach may include subsoil sensor which can monitor changes in soil pressure and moisture conditions. The sensor data can be sent to a computer module which can process the data using a machine learning model predicting the soil density around a subsoil crop and the yield of the subsoil crop. A soil maintenance plan can be generated from the soil density prediction and/or the crop yield prediction. The soil maintenance plan can be sent to soil management robots, which can execute the soil maintenance plan.

An instrumented indentation apparatus and instrumented indentation method, for use in instrumented indentation, employ a flat-ended indenter (punch). Force-displacement data of a loading operation, in which a sample is indented using the indenter, and the known value of the effective radius of the end surface of the indenter, are used to calculate values of stress and strain. The entire stress-strain curve for the sample may be produced from these values.

A method according to the present invention, it is possible to accurately measure the stretch-flangeability of sheet metal materials without size effects even when a small amount of specimen is used, compared with the stretch-flangeability established as an international standard, and to measure the stretch-flangeability in the local region. The method according to the present invention includes (a) performing a computer simulation of a small-scale specimen having a predetermined size by using finite element analysis to determine a size of the small-scale specimen; (b) using a standard-scale specimen having the same material as the small-scale specimen specified in the step (a) to perform a punching process specified in the standard testing method; (c) observing a distribution pattern of shearing defects in a hole-edge region of the specimen having performed the punching process, and evaluating a hole expansion ratio; (d) comparing the hole expansion ratio and the distribution pattern of shearing defects between the small-scale specimen and the standard-scale specimen to verify measurement reliability for the stretch-flangeability of the small-scale specimen; and (e) using the size of the small-scale specimen having verified the measurement reliability to evaluate stretch-flangeability.

The disclosed method includes, from a topographic map showing, for a set of points {x} located in a midplane of the fracture surface, a height of the fracture surface h relative to the midplane: a step of determining, for each point x on the topographic map, a quantity .sub. representative of an average difference in height).sub.IxI between the height h of the fracture surface at point x in question and the height h of the fracture surface at one or more points {x+x} located inside a circle of radius centered on point x in question, a step of determining, according to a test distance r, a spatial correlation function C representing a spatial correlation between points {x} and points {x+x} such as IxI=r, and a step of determining a correlation length from the spatial correlation function C.

A non-transitory computer readable storage medium with a destruction prediction program causing a computer to determine destruction prediction of a resin molding, and to function as a first calculation portion that calculates a maximum value of an equivalent strain that occurs in a cutout bottom and an inclination of an equivalent strain by applying, to a 3D test piece model of a test piece, a load at breaking the test piece, a threshold set portion that sets a threshold E of destruction progress based on the maximum value and the inclination, a second calculation portion that calculates a maximum value of an occurring equivalent strain and an inclination of an equivalent strain by applying a load to the 3D target model, and a destruction determination portion that determines whether or not destruction occurs based on the maximum value and the inclination, and the threshold.

The invention involves a method for testing a damage tolerance property in an aluminum alloy part with the following steps: measure at least one property representative of a the part's tensile strength; use the property measured in step a) as input datum (x.sub.i) of a neural network estimator; estimate, using the estimator, the representative property of the part's tensile strength; the method being characterized in that it includes: consideration of an acceptance threshold and comparison of the property estimated at step c) to the acceptance threshold, taking into account a confidence interval; based on the comparison: consider that the part passes the test; or consider that the part does not pass the test.

A method of controlling a mechanical testing instrument includes estimating a young's modulus, and applying force during a first time interval then comparing distance measured to expected distance; predicting a distance based on a first slope applying displacement distance and recalculating the slope; providing a corrected force applied for the proper displacement based on measured modulus and correction factor and adjusting into time and distance coherence; applying a force versus time regime interval and predict deformation at the end of the second interval measuring true deformation distance after the next interval; calculating the true slope based on the extrapolated actual slope; calculating a slope to apply for desired distance; and repeating measurement and correction steps, using the actual slope as the prediction basis. A system for carrying out the method is also disclosed using a data acquisition board.