Experimental Tests Research Articles

Strengthening of reinforced concrete slabs using carbon fiber reinforced polymers rods and concrete jacket with a mechanical anchorage system

This study presented the development of a new method for strengthening of Reinforced Concrete (RC) slabs using Carbon Fiber Reinforced Polymer rods (CFRP) and an Ultra-High Performance Fiber Reinforcement Concrete (UHPFRC) external jacket with a Mechanical Anchorage System (MAS). The mechanical anchorage system includes two components: high-carbon steel plates and the Mechanical Expansion Anchorage Bolt System (MEABS), and it’s employed to prevent any premature de-bonding between the existing concrete surface and the externally strengthening layers (CFRP rods and UHPFRC jacket). The efficiency of the proposed strengthening method was evaluated through conducting an experimental test on a few fortified slabs by applying cyclic loads using a dynamic actuator. For this purpose, three distinct concrete slabs were tested to assess various design parameters, including a control slab, a strengthened slab with the UHPFRC jacket only, and a strengthened slab with CFRP bars at the bottom of the slab with an external UHPFRC jacket. The results of experimental tests reveal that the proposed strengthening system significantly enhanced the load capacity of the slab and prevented premature debonding failures between the old concrete of the slab and the new UHPFRC layer until the stage of slab failure. Accordingly, the new proposed strengthening system played a crucial role in enhancing the tension zone of the slabs and delaying the occurrence of diagonal crack loads. On the other hand, embedding CFRP bars within the UHPFRC jacket in the strengthened slab led to a notable enhancement of 82 % in the ultimate load capacity of the slab. The FE and analytical models were developed to predict the behavior of the specimens. The models' outcomes were in good agreement with the experimental data. Consequently, the new proposed strengthening system emerges as a reliable technique for enhancing the performance of reinforced concrete slabs, eliminating the risk of debonding between old and new parts.

Visualizing flow dynamics and restart of Carbopol gel solutions in tube and parallel-plates geometries with wall slip.

The present study examines the impact of slip in Carbopol solutions during the restart flow in pipelines utilizing in situ visualization techniques. Rheological tests were conducted using smooth and hatched parallel plate geometries to obtain the rheological characteristics of the solutions. The behavior of the solutions in the creep tests is compared with those in the experimental unit. Three flow regimes were identified through rheological and experimental setup tests: non-flow, slip, and yielded. The slip regime allowed the establishment of a slip static yield stress value, indicating significant deformation states, and a restart pressure decrease of about 61% when compared to the static yield stress. The flow dynamics under the wall slip effect is captured by velocity profiles, velocity contour maps and velocity gradient. Transient correlations of the scaling law type were determined, with wall slip in proportion to the velocity gradient and wall shear stress. Additionally, the concentration of viscoplastic material in the solution increased the scaling law index. This research seeks to provide valuable findings by quantifying the effects of apparent wall slip through in situ measurements. Such insights are crucial for designing and managing pipeline transport systems that handle yield stress fluids, applicable across various industries including cosmetics, food processing, and the production of waxy oils.

High-resolution monitoring of soil infiltration using distributed fiber optic

Monitoring the infiltration process in soil is of great importance in various fields. However, the majority of existing infiltration monitoring methods have certain limitations that hinder their ability to meet the technical requirements for continuous spatial monitoring of the infiltration process. To address this issue, this study proposes a new method for achieving spatially continuous monitoring of the infiltration process. This method employs the improved Active Heating Fiber Optics (AHFO) technique as the underlying mechanism and utilizes Optical Frequency Domain Reflectometry (OFDR) monitoring technology characterized by exceptionally high spatial resolution and monitoring sensitivity. The proposed method, referred to as Active Heating Optical Frequency Domain Reflectometry (AH-OFDR). The feasibility of AH-OFDR was validated through a set of experimental tests, involving the installation of optical fibers within cylindrical soil samples for infiltration monitoring. A comparison was conducted between the infiltration patterns obtained through AH-OFDR and those acquired using the well-established Distributed Temperature Sensing (DTS) method. Additionally, the temperature distribution within the sample during the infiltration process was monitored by employing infrared thermography technology. The experimental results demonstrated an excellent agreement between the infiltration patterns obtained through AH-OFDR and DTS, reaffirming the viability and accuracy of AH-OFDR for soil infiltration monitoring. However, when compared to DTS, AH-OFDR excels in achieving dynamic monitoring of water content variations at a spatial resolution as fine as the centimeter level, empowering high-resolution and continuous monitoring. The changes in the soil temperature field recorded by the infrared thermography system further confirm the accuracy of the AH-OFDR monitoring results.

Theoretical and experimental investigations on a data-driven trajectory planning scheme for dynamic shape control of piezo-actuated compliant morphing structures

Piezo-actuated compliant morphing structures can transmit motion and force via elastic deformation with lower weight, simplified design, and higher accuracy, a typical example is the variable camber wing. However, the rapid shape change of compliant structures is a challenging control problem because it often results in a high level of vibration due to the structural flexibility necessary to achieve the morphing requirement. This study presents a model-free data-driven trajectory planning approach based on spline curves and surrogate-based optimization (SBO) to obtain smooth “rest-to-rest” morphing trajectories. The macro-fiber composite (MFC) patches are used for piezoelectric actuators to generate elastic deformation. The flexible beam and variable camber wing are used for both linear numerical simulation and experimental tests with various nonlinearities and uncertainties. An optimization criterion is proposed to minimize both transient and residual vibrations during the “rest-to-rest” motion. An extraordinarily terminal displacement error function is added to eliminate the effects of the hysteresis and creep of the actuator. The control inputs, i.e., voltage profiles for the MFCs, are defined using cubic spline curves via only a few control points. Then, the optimization problem is solved by employing a Kriging surrogate model-based algorithm integrated with the expected improvement (EI) infilling-sampling criterion, which constructs an efficient algorithm similar to reinforcement learning. The optimal morphing trajectories can be highly efficiently obtained by using only 4 control points and less than 150 samplings. The experimental results of both the plate model and the variable camber wing model show that the proposed method can not only achieve a smooth dynamic morphing trajectory with minimized vibration but also automatically compensate for hysteresis and creep. The proposed method provides an effective means for the rapid realization of an optimized morphing trajectory for compliant morphing structures.

US & MR/CT Image Fusion with Markerless Skin Registration: A Proof of Concept.

This paper presents an innovative automatic fusion imaging system that combines 3D CT/MR images with real-time ultrasound acquisition. The system eliminates the need for external physical markers and complex training, making image fusion feasible for physicians with different experience levels. The integrated system involves a portable 3D camera for patient-specific surface acquisition, an electromagnetic tracking system, and US components. The fusion algorithm comprises two main parts: skin segmentation and rigid co-registration, both integrated into the US machine. The co-registration aligns the surface extracted from CT/MR images with the 3D surface acquired by the camera, facilitating rapid and effective fusion. Experimental tests in different settings, validate the system's accuracy, computational efficiency, noise robustness, and operator independence.

Comparative assessment of thermal oils and water as working fluids in parabolic trough collectors for enhanced solar power generation

Examining the thermal behavior of specific working fluids, namely Syltherm800 and TherminolVP-1, in parabolic trough collectors (PTCs) is imperative for enhancing power generation. This study addresses a crucial gap by conducting computational fluid dynamics simulations through COMSOL Multiphysics software and experimental tests to explore the advantages of utilizing thermal oils over water as a working fluid in PTCs. Experimental tests were performed on a water-based PTC in Iraq to validate the numerical model, considering various operating conditions such as input temperature (323.15–423.15 K) and mass flow rates (0.00926–0.0556 kg/s). Key parameters including output temperature, thermal efficiency, useful heat, and total heat losses were evaluated. The numerical model was validated against experimental data, showing good agreement with an overall discrepancy of 1.7% for the current experiments and 3.18% for literature results. The results indicated that Syltherm800, particularly with a high mass flow rate, outperformed TherminolVP-1 and water in terms of overall thermal performance. The optimal PTC thermal efficiency was achieved in July with a mass flow rate of 0.0556 kg/s and an input temperature of 348.15 K. The optimal range for PTC thermal efficiency over four months was between 50% and 70%. The endorsement of thermal oils in PTCs is supported by their low vapor pressure, superior thermal stability, and extended lifespan.

Mechanical responses and fracturing behaviors of coal under complex normal and shear stresses, Part I: Experimental results

This work presents experimental tests based on coal collected from a coal mine based underground water reservoir (CMUWR). The mechanical responses of dry and water-soaked coal samples under the complex normal and shear stresses under multi-amplitude and variable frequency is investigated. The experimental results reveal the effects of stress path, water soaking and frequency on deformation, energy dissipation, secant modulus and shear failure surface roughness. The experimental results show that when normal and shear stresses are applied simultaneously, there is a significant competitive relationship between them. On the dominant side, the strain rate will be significantly increased. The sample under a loading frequency of 0.2 Hz exhibits a longer fatigue life. During the cyclic shear test, the shear strain of the water-soaked sample is higher than that of the dry samples. The average roughness coefficient of failure surface exhibits an increasing pattern with increase in shear strength, the elevated roughness of a shear surface is advantageous in constraining shear displacements of specimens, thereby lowering the energy dissipation. This study can provide theoretical and practical implications for a long-term safety evaluation of CMUWR.

Improving stability in hybrid fire testing: Advancements in analysis method and software implementation

In large-scale structural fire resistance tests, the interaction between the individual elements and the surrounding structure causes discrepancies in behaviour compared to single-element fire tests. Large-scale tests of real structures are challenging due to financial and time limitations. To bridge this gap, the concept of “Hybrid Fire Testing (HFT)” emerges, where a portion of the structural system (i.e., physical substructure) is experimentally tested while the remaining structure (i.e., numerical substructure) is analyzed numerically. The primary challenges in HFT involve ensuring stability throughout the analysis by considering the varying stiffness of the fire-exposed element during the test and establishing a versatile communication platform between the physical substructure (PS) and numerical substructure (NS) components. This paper presents a comprehensive HFT framework, implemented within a user-friendly software interface, facilitating both virtual and experimental testing. The software incorporates a new method addressing stability concerns by predicting PS stiffness during the test, achieving convergence within a limited number of iterations. Additionally, the framework includes a communication platform utilizing internet protocols (IP) and COM ports for rapid and easy connection to diverse experimental control systems and finite element software packages. The functionality of the developed software is validated through its successful application in an HFT conducted on a 3-story steel structure within a simulated environment. Both force-controlled and displacement-controlled approaches confirm the method’s adaptivity to the employed test procedures.

Effect of additively manufactured polymeric inserts on impact response of construction safety helmets

Purpose Struck-by accidents (i.e. being hit by a falling object) are a leading cause of traumatic brain injuries in the construction industry. Despite the critical role of hard hats in minimizing such injuries, their overall design has not appreciably changed in decades. Therefore, this study aims to explore the potential benefits of modifying commercially available hard hat designs by incorporating a compliant cantilever and a sacrificial, energy-absorbing structure to enhance their protective capabilities against impacts. Design/methodology/approach This study involved conducting experimental impact tests to obtain the head acceleration attenuation using hard hats with a variety of compliant cantilever lattice insert designs. These lattice inserts were additively manufactured using three polymeric materials, including polylactide (PLA), acrylonitrile butadiene styrene, high-impact polystyrene and three porosity levels. A Hybrid III head/neck assembly was fitted with each hard hat design, and experimental drop tests were conducted using a 1.8-kg steel impactor dropped from 1.83 m. The maximum acceleration and head injury criterion (HIC) values were obtained for each test. Findings Analysis of variance revealed that HIC was significantly reduced for all lattices with 56% porosity (p < 0.023) compared to the control (unmodified) hard hat. The most effective insert was found to be a PLA insert with 56% porosity, which reduced the HIC value by 38% compared to the control (unmodified) hard hat, with a statistically significant p-value of 0.018. Originality/value The data present in this study reveals that simple and inexpensive modifications can be made to existing hard hat designs to reduce injury risk from overhead impacts.

Dehydration of Onion Slices for Food Processing Application Using IoT based Smart Solar Drying System

Abstract Indian onion producers experience significant economic losses as a result of the unpredictable fluctuations in onion prices during the harvesting and post-harvest stages. In order to address these difficulties and increase farmers' earnings, the transformation of onions into value-added goods such as onion paste, onion powder, onion sauce, and onion oil has emerged as a possible option. The objective of this project is to create a smart solar drying system based on IoT technique specifically designed for the dehydration of recently harvested red onions. In April 2023, a series of five experimental tests were carried out, examining the effects of different onion slice thicknesses ranging from 2mm to 4mm, with intervals of 0.5mm. Each trial consisted of running the dryer for a duration of 9 hours, specifically from 9:00 am to 6:00 pm, throughout the daylight hours for three consecutive days. The experiment involved evaluating different drying characteristics, such as moisture content on dry and wet bases, shrinkage ratio, and thermal efficiency. The drying time required to achieve a 10% moisture level (w.b.) was reduced by 30.19%, 16.98%, 11.32%, and 3.77% when comparing a 4mm slice thickness to thinner alternatives of 2mm, 2.5mm, 3mm, and 3.5mm, respectively. The dryer had a superior thermal efficiency of 27.89% when the thickness was 2mm, in contrast to 19.50% when the thickness was 4mm. Significantly, onions that were dehydrated from slices measuring 2mm and 2.5mm in thickness shown exceptional suitability for the production of powdered onion.

Reliability and robustness of a novel preclinical torsional wave-based device for stiffness evaluation

In this work, we present a novel preclinical device utilizing Torsional Wave Elastography (TWE). It comprises a rotational actuator element and a piezoceramic receiver ring circumferentially aligned. Both allow the transmission of shear waves that interact with the tissue before being received. Our main objective is to demonstrate and characterize the reliability, robustness, and accuracy of the device for characterizing the stiffness of elastic materials and soft tissues. Experimental tests are performed using two sets of tissue mimicking phantoms. The first set consists of calibrated CIRS gels with known stiffness value, while the second test uses non-calibrated manufactured phantoms. Our experimental observations show that the proposed device consistently and repeatably quantifies the stiffness of elastic materials with high accuracy. Furthermore, comparison with established techniques demonstrates a very high correlation (> 95%), supporting the potential medical application of this technology. The results obtained pave the way for a cross-sectional study aiming to investigate the correlation between gestational age and cervical elastic properties during pregnancy.

Experimental Tests on External and Terminal Ballistics of Different Types of Projectiles Fired From .38 SPL Caliber Cartridges and Study of Permanent Cavitation in Anatomical Modeling With 10% Ballistic Gelatin.

The present study investigated the main morphological differences between the permanent cavities formed by 4 different types of projectiles fired from .38 SPL caliber cartridges in blocks of 10% ballistic gelatin with standardized formulation (Federal Bureau of Investigation Protocol), all fired from the same distance and from the same firearm, associated with its performances in external and terminal ballistics. The velocity or the mass presented by a firearm projectile will not always be solely responsible for the final configuration of the permanent cavity, in which the projectile design, for example, is an equally important element. Each type of projectile tested in the present work generated a different kind of permanent cavity, but they also varied in velocity (m/s) and energy (J). The use of 10% ballistic gelatin in scientific research that seeks to investigate the external and terminal ballistics of projectiles can contribute to the practice of professionals working either in forensic pathology or applied ballistics scenarios, as they can experimentally simulate the events that can occur in the tissues of victims inflicted by gunshot wounds, which also allows important applications in the medical, commercial, civil, and military sectors that deal with products and technologies related to the human body.

Meso-scale Study of Bond Behavior between Ribbed Steel Rebar and Fiber-reinforced Cementitious Composite Considering Rebar Rib Geometry

This study aims to develop a meso-scale finite element approach to investigate the pull-out behavior of ribbed steel rebar and fiber-reinforced cement composites. We considered separately the three phases of steel fibers, cement composite matrix, and rebar within the meso-scale finite element model. A random distribution of fibers was generated in the matrix based on the geometric characteristics of the fibers and their volume fraction. By employing the interfacial transition zone (ITZ) model, the interaction between rebar and fibers with cement composite was simulated. Experimental pull-out tests were conducted to determine the parameters of the model. A meso-scale finite element model was validated and the effect of rebar diameter and fiber volume fraction on the bond behavior of rebar with fiber-reinforced cement composites was examined. In accordance with the experimental results, the bond-slip curve obtained with the meso-scale finite element model can be divided into five areas: non-slip, slight slip, splitting, decreasing, and residual. Additionally, it can be observed that fiber-free cement composites fail by splitting, whereas specimens containing fibers fail by sliding. This numerical model is therefore able to predict and estimate the influence of a variety of parameters on the pull-out response between fiber-reinforced cement composite and ribbed bar and failure mechanisms without the need for expensive and time-consuming testing.

How Often Should Microbial Contamination Be Detected in Aircraft Fuel Systems? An Experimental Test of Aluminum Alloy Corrosion Induced by Sulfate-Reducing Bacteria

Microbial contamination in aircraft fuel-containing systems poses significant threats to flight safety and operational integrity as a result of microbiologically influenced corrosion (MIC). Regular monitoring for microbial contamination in these fuel systems is essential for mitigating MIC risks. However, the frequency of monitoring remains a challenge due to the complex environmental conditions encountered in fuel systems. To investigate the impact of environmental variables such as water content, oxygen levels, and temperature on the MIC of aluminum alloy in aircraft fuel systems, orthogonal experiments with various combinations of these variables were conducted in the presence of sulfate-reducing bacteria. Among these variables, water content in the fuel oil demonstrated the most substantial influence on the corrosion rate of aluminum alloys, surpassing the effects of oxygen and temperature. Notably, the corrosion rate of aluminum alloys was the highest in an environment characterized by a 1:1 water/oil ratio, 0% oxygen, and a temperature of 35 °C. Within this challenging environment, conducive to accelerated corrosion, changes in the corrosion behavior of aluminum alloys over time were analyzed to identify the time point at which MIC intensified. Observations revealed a marked increase in the depth and width of corrosion pits, as well as in the corrosion weight-loss rate, starting from the 7th day. These findings offer valuable insights for determining the optimal frequency of microbial contamination detection in aircraft fuel systems.

Cabello's nonlocality argument for multisetting high-dimensional systems and its experimental test

Cabello's nonlocality argument for multisetting high-dimensional systems and its experimental test

Modelling the Acoustic Properties of Baffles Made of Porous and Fibrous Materials

The research described in the article addresses the problem of measurement, prediction and practical use of the acoustic properties of materials determined in an impedance tube. The aim of the research was to develop a simple calculation model for the insertion loss of small machinery enclosures, based on the normal incidence sound transmission loss and the normal incidence sound absorption coefficient of porous and fibrous materials. Both experimental and model tests were carried out on materials such as mineral wool, melamine foam and rebonded polyurethane foam. Assessing the absorption properties of the tested porous and fibrous materials was performed using selected theoretical models, relating the calculations of the normal incidence sound absorption coefficient to measurements of this parameter conducted using an impedance tube. The application of the modified Allard and Champoux model brought the best results with the smallest discrepancies of the obtained results in relation to the experimental tests. Assessing the sound-insulating properties of the tested mineral wool was carried out using the proposed calculation model for the normal incidence sound transmission loss, relating the obtained results to measurements conducted using an impedance tube. The assessment of the sound-insulating properties of porous and fibrous materials was performed using the proposed calculation model for insertion loss, which was validated using two prototype test stands for determining the insertion loss of cubic enclosures, in this case with walls made of porous and fibrous materials. Satisfactory results were obtained for engineering applications in the calculation results using the proposed models with respect to measurements. The results may have practical applications in assessing the effectiveness of acoustic enclosures, in which the basic construction material is an appropriate porous or fibrous plate, selected to have both sound-absorbing and sound-insulating properties.

High-quality ghost imaging based on undersampling natural order Hadamard source

Abstract Improving the imaging speed of ghost imaging is one of the main ways to leverage its advantages in sensitivity and imperfect spectral regions for practical applications. Due to the proportional relationship between image resolution and measurement times, when the image pixels are large, the measurement times also increase, making it difficult to achieve real-time imaging. Therefore, a high-quality ghost imaging method based on undersampling natural order Hadamard is proposed. This method utilizes the characteristics of the Hadamard matrix under undersampling conditions where image information can be fully obtained but overlaps, and utilizes deep learning to extract the aliasing information from the overlapping results to obtain the true original image information. We conducted numerical simulations and experimental tests on binary and grayscale objects under undersampling conditions, demonstrating the effectiveness and scalability of this method. This method can significantly reduce the number of measurements required for obtaining high-quality image information and promote application promotion.

Frequency reconfigurable slot antenna utilizing solid-state plasma S-PIN diodes: simulation and experimental analysis

Abstract This article examines the feasibility of integrating solid-state plasma surface p-i-n (S-PIN) diodes into on-chip slots using silicon-on-insulator (SOI) technology. Two categories of solid-state plasma S-PIN diodes are characterized. Simulations analyze the current-voltage (I-V) characteristics, carrier concentrations, potential distribution, and thermal considerations of both single and dual S-PIN diodes, with optimization of their structural parameters and sizes. Experimental tests on fabricated S-PIN diodes of varying sizes with bias lines embedded in the on-chip slots show favorable I-V characteristics for both types of diodes. The measured results closely align with simulation predictions for the diodes' conduction onset voltages. Additionally, a cavity-backed slot antenna (CBSA) is proposed to evaluate and compare radiation characteristics resulting from integrating different types of S-PIN diodes.

Comparative Analysis of Machine Learning Models for Predicting the Mechanical Behavior of Bio-Based Cellular Composite Sandwich Structures

The growing demand for sustainable materials has significantly increased interest in biocomposites, which are made from renewable raw materials and have excellent mechanical properties. The use of machine learning (ML) can improve our understanding of their mechanical behavior while saving costs and time. In this study, the mechanical behavior of innovative biocomposite sandwich structures under quasi-static out-of-plane compression was investigated using ML algorithms to analyze the effects of geometric variations on load-bearing capacities. A comprehensive dataset of experimental mechanical tests focusing on compression loading was employed, evaluating three ML models—generalized regression neural networks (GRNN), extreme learning machine (ELM), and support vector regression (SVR). Performance indicators such as R-squared (R2), mean absolute error (MAE), and root mean square error (RMSE) were used to compare the models. It was shown that the GRNN model with an RMSE of 0.0301, an MAE of 0.0177, and R2 of 0.9999 in the training dataset, and an RMSE of 0.0874, MAE of 0.0489, and R2 of 0.9993 in the testing set had a higher predictive accuracy. In contrast, the ELM model showed moderate performance, while the SVR model had the lowest accuracy with RMSE, MAE, and R2 values of 0.5769, 0.3782, and 0.9700 for training, and RMSE, MAE, and R2 values of 0.5980, 0.3976 and 0.9695 for testing, suggesting that it has limited effectiveness in predicting the mechanical behavior of the biocomposite structures. The nonlinear load-displacement behavior, including critical peaks and fluctuations, was effectively captured by the GRNN model for both the training and test datasets. The progressive improvement in model performance from SVR to ELM to GRNN was illustrated, highlighting the increasing complexity and capability of machine learning models in capturing detailed nonlinear relationships. The superior performance and generalization ability of the GRNN model were confirmed by the Taylor diagram and Williams plot, with the majority of testing samples falling within the applicability domain, indicating strong generalization to new, unseen data. The results demonstrate the potential of using advanced ML models to accurately predict the mechanical behavior of biocomposites, enabling more efficient and cost-effective development and optimization processes in the field of sustainable materials.

Experimental implementation of skeleton tracking for collision avoidance in collaborative robotics

AbstractCollaborative robotic manipulators can stop in case of a collision, according to the ISO/TS 15066 and ISO 10218-1 standards. However, in a human-robot collaboration scenario where the robot and the human share the workspace, a better solution with concerns to production and operator safety would be to perceive in advance the presence of an obstacle and be able to avoid it, thereby completing the task without halting the robot. In this paper, an obstacle avoidance algorithm is tested using a sensor system for real-time human detection; the operator represents a potential dynamic obstacle that can interfere with the robot motion. The sensor system consists of three RGB-D cameras. A custom software framework has been developed in Python exploiting machine learning tools for human skeleton detection. The coordinates of the human body joints relative to the manipulator base are used as input to the obstacle avoidance algorithm. The use of multiple sensors makes it possible to limit the occlusion problem; in addition, the choice of non-wearable sensors goes in the direction of better operator comfort. A series of experimental tests were performed to verify the accuracy of skeleton detection and the ability of the system to avoid obstacles in real time. The human motion caption system, in particular, was validated through a comparison with a commercial system based on wearable IMU sensors widely used and validated in motion capture. There is an NRMSE of $$3.23\%$$ 3.23 % for the RGB-D camera-based skeleton detection system, against an NRMSE of $$12.23\%$$ 12.23 % for the IMU wearable sensor system. Test results confirm that the system is able to avoid collisions with the human body under various conditions, static or dynamic, ensuring a minimum safety distance to any part of the manipulator. In 44 tests in which the operator moves around the robot with possible collisions (at a speed typical of manufacturing operations), the minimum operator-robot distance averaged $$208\,\textrm{mm}$$ 208 mm , being $$200\,\textrm{mm}$$ 200 mm the limit safety distance set by algorithm.