Kalibrasi Model Soil Moisture Accounting dengan Software HEC-HMS di Stasiun Debit Pasir Pangaraian

This research aims to compare the results of the calibration of the Soil Moisture Accounting (SMA) model using Percent Error in Volume (PEV) and Peak Weighted Root Mean Square Error (RMSE). The SMA model calibration uses the HEC-HMS (Hydrologic Engineering Center – Hydrologic Modeling System). There are 12 calibrated parameters by automatic calibration. The input data are the area of ​​the watershed, daily rainfall, daily discharge data and climatological data. The data used is data from 2008 to 2017. The results show that PEV performance shows good results. While the RMSE showed poor results. PEV results are best at 7 years of calibration and 3 years of verification. The length of the calibration data has not affected the verification results.

Raspy-Cal: A Genetic Algorithm-Based Automatic Calibration Tool for HEC-RAS Hydraulic Models

While automatic calibration programs exist for many hydraulic models, no user-friendly and broadly reusable automatic calibration system currently exists for steady-state HEC-RAS models. This study highlights development of Raspy-Cal, an automatic HEC-RAS calibration program based on a genetic algorithm and implemented in Python. It includes a graphical user interface and an interactive command-line interface, as well as libraries readily usable by other programs. As a case study, Raspy-Cal was used to calibrate a model of the Los Angeles River in California and its two major tributaries. We found that Raspy-Cal matched the accuracy of manual calibrations in much less time and without manual intervention, producing a Nash–Sutcliffe Efficiency of 0.89 or greater within several hours when run for 100 iterations. Our analysis showed that the open-source freeware facilitates fast and precise calibration of HEC-RAS models and could serve as a basis for future software development. Raspy-Cal is available online in source and executable form as well as through the Python Package Index.

Design and Application of Automatic Calibration Device for Multi-Channel Resistance Strain Gauge Indicator

In this paper, an automatic calibration device for multi-channel resistance strain gauge indicator is designed and its applicability and measurement accuracy are verified at laboratory. The calibration done by original resistance bridge calibrator is time-consuming for its manual operation and complex calibration process. With the intent to increase calibration efficiency, an automatic channel switch device was developed, and the resistance bridge calibrator was automated. The designed calibration device is completely computer controlled enabling a sequence of unmanned measurements. The calibration device was verified at laboratory that the maximum of error is 0.072%. It was applied to calibrate a 60-channel resistance strain gage indicator to approve its practical applicability. The result shows that the designed calibration device can realize automatic calibration and the efficiency is increased by 40%.

Automatic Calibration of a Geomechanical Model from Sparse Data for Estimating Stress in Deep Geological Formations

Summary In this study, we demonstrate geomechanical modeling with fully automatic parameter calibration to estimate the full geomechanical stress fields of a prospective US CO2 storage site, based on sparse measurement data. The goal is to compute full stress tensor field estimates (principal stresses and orientations) that are maximally compatible with observations within the constraints of the model assumptions, thereby extending point-wise, incomplete partial stress measurement to a simulated full formation stress field, as well as a rough assessment of the associated error. We use the Perch site, located in Otsego Country, Michigan, as our case study. Input data consists of partial stress tensor information inferred from in-situ borehole tests, geophysical well logs and processing of seismic data. A static earth model of the site was developed, and geomechanical simulation functionality of the open-source MATLAB Reservoir Simulation Toolbox (MRST) used to model the stress field. Adjoint-based nonlinear optimization was used to adjust boundary conditions and material properties to calibrate simulated results to observations. Results were interpreted through a Bayesian framework. The focus of this article is to demonstrate how the fully automatic calibration procedure works and discuss the results obtained but does not attempt a detailed analysis of the stress field in the context of the proposed CO2 storage initiatives. Our work is part of a larger effort to non-invasively determine in-situ stresses in deep formations considered for CO2 storage. Guided by previously published research on geomechanical model calibration, our work presents a novel calibration approach supporting a potentially large number of linear or nonlinear calibration parameters, in order to produce results optimally agreeing with available measurements and thus extend partial point-wise estimates to full tensor fields compatible with the physics of the site.

SPACE CALIBRATION OF THE ROBOT SYSTEM IN PUNCTURE SURGERY

Traditional manual puncture surgery has low positioning accuracy and poor stability. Moreover, the computed tomography method can cause strong radiation damage. Therefore, this study intends to establish a robotic system in puncture surgery, which is based on optical registration to improve safety, accuracy, and efficiency. As the accuracy of surgical space calibration influences the accuracy of the surgical system, this study proposes an improved automatic calibration algorithm for linear rotation. The algorithm can reduce error caused by manual calibration and system noise. Recalibration is not required provided that the pose of the digital reference frame is unchanged, thereby improving accuracy and efficiency. The proposed algorithm is experimentally verified to prove its effectiveness. Results show that the average errors of position and posture are 0.25[Formula: see text]mm and 0.2∘, respectively. The accuracy of calibration fully meets the needs of surgery.

Measuring the diameter of a cylinder with automatic calibration

The work aims at developing a method for measuring the diameter of cylindrical objects, eliminating the need for calibration and verification of the measurement system during operation. The system for measuring the diameter of cylindrical objects contains a photodetector and a light source located on opposite sides of the measured object to implement the shadow method. The proposed method is based on the measurement of two reference cylinders located in the measuring area for automatic calibration of the system at each measurement. It is shown that the proposed method provides stable reliable measurements with an error of less than 2 μm for the diameter of the measured cylindrical objects of up to 10 mm.