Dr. Ermias Koricho, completed his PhD in Mechanical Engineering (Mechanics) at Polytechnic University of Turin (Politecnico Di Torino) in 2012. He has conducted research in the area of: vehicle lightweight design and crashworthiness, structural optimization, multi-materials joining (reversible adhesives, bolted, hybrid), multi-functional composite, plastic and adhesives materials, applications of nondestructive evaluation techniques, composite manufacturing and repair. Dr. Koricho has research experiences in automotive industry and composite materials and structures research centers.
Areas of Expertise (1)
Vehicle Design & Testing
Politecnico di Torino: Ph.D.
Bahir Dar University: B.S.
Addis Ababa University: M.A.
E. Koricho et al.
2017 Guided wave structural health monitoring uses sparse sensor networks embedded in sophisticated structures for defect detection and characterization. The biggest challenge of those sensor networks is developing robust techniques for reliable damage detection under changing environmental and operating conditions (EOC). To address this challenge, we develop a novelty classifier for damage detection based on one class support vector machines. We identify appropriate features for damage detection and introduce a feature aggregation method which quadratically increases the number of available training observations. We adopt a two-level voting scheme by using an ensemble of classifiers and predictions. Each classifier is trained on a different segment of the guided wave signal, and each classifier makes an ensemble of predictions based on a single observation. Using this approach, the classifier can be trained using a small number of baseline signals. We study the performance using Monte-Carlo simulations of an analytical model and data from impact damage experiments on a glass fiber composite plate. We also demonstrate the classifier performance using two types of baseline signals: fixed and rolling baseline training set. The former requires prior knowledge of baseline signals from all EOC, while the latter does not and leverages the fact that EOC vary slowly over time and can be modeled as a Gaussian process.
E. Koricho et al.
2017 Robust and quantitative non-destructive evaluation (NDE) is essential for damage characterization in advanced materials, such as glass fiber reinforced polymer (GFRP) composites. Previous work demonstrated the capabilities of an optical transmission scanning (OTS) system, including an advanced image processing algorithm, for rapid and non-contact NDE of healthy and impacted GFRP samples. The number of delaminations and their contours in the test samples were accurately identified. In this paper, damage was introduced in GFRP samples by low velocity impacts of different energies, and OTS was validated by comparing the inspection results with conventional NDE techniques, including pulse-echo ultrasonic testing (UT) and UV dye penetrant testing (UV DPT). In addition, quantitative comparisons of damage severity were made for OT scans and UT C-scans by converting images to a normalized damage metric. Experimental results demonstrated that the estimated extent of impact damage agreed very well for all used techniques. Thus, OTS combines the cost-effectiveness and rapidity of qualitative techniques (e.g., UV DPT) with the more robust and comprehensive data analysis provided by quantitative methods (e.g., UT).
E. Koricho et al.
2017 This paper investigates the mechanical behavior of three selected steel materials which are considered to be the bulk material of front most bumper beam of a vehicle that is suddenly loaded in the quasi-static range. Thirty-six constant strain rate uniaxial tension tests were performed. The test was performed on a HUALONG electro-hydraulic universal testing machine at four strain rates (3.33 × 10-3,3.33 × 10-2, 3.33 × 10-1, 3. 33s-1). The FEM which is ABAQUS/CAE is used to simulate the bumper subsystem using the three selected steel. The outcome shows that ultimate tensile strength (UTS) increase with an increase in strain rate and high alloy steel (HAS) material has the maximum mean UTS. The FEM in the post -processing stage gives the minimum displacement and maximum strain energy for HAS material when compared to the other two materials. Finally, from both experimental and ABAQUS explicit analysis the result shows HAS material is better suit for the bumper beam application.
E. Koricho et al.
2016 Non-destructive evaluation (NDE) techniques that can measure both surface and subsurface defects are of critical importance in evaluating the integrity of GFRP composites. In the present work, optical transmission scanning (OTS) technique was proposed for acquiring high-resolution, rapid, and non-contact OT (optical transmittance)-scans of pristine and impacted GFRP samples. Advanced data analysis was developed and implemented to identify the number of delaminations at every scan position. The results agreed very well with the actual number and extent of delaminations observed directly from a cross-section of the specimen. Overall, the presented technique lays the groundwork for cost-effective, non-contact, rapid, and quantitative NDE of GFRP composite structures.
2016 Damage induced in polymer composites by various impacts must be evaluated to predict a component’s post-impact strength and residual lifetime, especially when impacts occur in structures related to human safety (in aircraft, for example). X-ray tomography is the conventional standard to study an internal structure with high resolution. However, it is of little use when the impacted area cannot be extracted from a structure. In addition, X-ray tomography is expensive and time-consuming. Recently, we have demonstrated that a kHz-rate laser-ultrasound (LU) scanner is very efficient both for locating large defects and evaluating the material structure. Here, we show that high-quality images of damage produced by the LU scanner in impacted carbon-fiber reinforced polymer (CFRP) composites are similar to those produced by X-ray tomograms; but they can be obtained with only single-sided access to the object under study. Potentially, the LU method can be applied to large components in-situ.