publications

2023

1. JMD

   Design space exploration and evaluation using margin-based trade-offs

   Al Handawi, Khalil, Brahma, Arindam, Wynn, David C., Kokkolaras, Michael, and Isaksson, Ola

   Journal of Mechanical Design 2023

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   Design space exploration and margin analysis can inform critical decisions early in engineering design, helping to handle the uncertainties of early design while ensuring design performance. In practice, the complexity of many products makes such decision-making challenging. This paper addresses the challenge with a new design framework that relies on the margin value method to evaluate sets of concepts that are combinatorially generated from an enhanced function-means tree. The basis for concept comparison is the margin value in each design alternative. The margin value method is expanded to address a broad class of design problems by using surrogate models and novel metrics for evaluating different conceptual alternatives. Visualization tools are introduced to support the evaluations. The efficacy of the framework is demonstrated using the design of a structural aero-engine component involving simulation models and uncertain load specifications. Overall, this paper shows how design concepts can be compared objectively and distilled to a set of alternatives that would retain their values throughout product development.

2022

1. Viruses

   Weekly Nowcasting of New COVID-19 Cases Using Past Viral Load Measurements

   Khalil, Athar, Al Handawi, Khalil, Mohsen, Zeina, Abdel Nour, Afif, Feghali, Rita, Chamseddine, Ibrahim, and Kokkolaras, Michael

   Viruses 2022

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   The rapid spread of the coronavirus disease COVID-19 has imposed clinical and financial burdens on hospitals and governments attempting to provide patients with medical care and implement disease-controlling policies. The transmissibility of the disease was shown to be correlated with the patient’s viral load, which can be measured during testing using the cycle threshold (Ct). Previous models have utilized Ct to forecast the trajectory of the spread, which can provide valuable information to better allocate resources and change policies. However, these models combined other variables specific to medical institutions or came in the form of compartmental models that rely on epidemiological assumptions, all of which could impose prediction uncertainties. In this study, we overcome these limitations using data-driven modeling that utilizes Ct and previous number of cases, two institution-independent variables. We collected three groups of patients (n = 6296, n = 3228, and n = 12,096) from different time periods to train, validate, and independently validate the models. We used three machine learning algorithms and three deep learning algorithms that can model the temporal dynamic behavior of the number of cases. The endpoint was 7-week forward number of cases, and the prediction was evaluated using mean square error (MSE). The sequence-to-sequence model showed the best prediction during validation (MSE = 0.025), while polynomial regression (OLS) and support vector machine regression (SVR) had better performance during independent validation (MSE = 0.1596, and MSE = 0.16754, respectively), which exhibited better generalizability of the latter. The OLS and SVR models were used on a dataset from an external institution and showed promise in predicting COVID-19 incidences across institutions. These models may support clinical and logistic decision-making after prospective validation.

2021

1. IEEE TETCI

   Optimization of Infectious Disease Prevention and Control Policies Using Artificial Life

   Al Handawi, Khalil, and Kokkolaras, Michael

   IEEE Transactions on Emerging Topics in Computational Intelligence 2021

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   The spread of an infectious disease such as COVID-19 is governed by complex social interactions that are challenging to model. Policy makers must take measures to control the spread of infection despite the unknowns that accompany a novel epidemic. The principles of artificial life govern the intricacies of social interaction through which diseases can spread. Agent-based models can capture these complexities for a subset of the population by defining the behavior of individual agents. While they can be computationally expensive for large populations, their outcomes are stochastic. Therefore, they can be used to test disease prevention policies, that can be difficult to simulate using deterministic approaches. We developed an agent-based model that is inspired by several interactive simulations on the internet for describing the COVID-19 pandemic. We define metrics to estimate the socio-economic cost of disease prevention policies on the population. We present a policy-making tool based on blackbox optimization and evolutionary computation that provides well-rounded intervention measures in terms of socio-economic cost and disease control. Several intervention measures are suggested by the algorithms with varying degrees of disease control and socio-economic cost. Policy makers can choose an intervention measure based on their preference. This research recommends combining computational intelligence principles and the use of mathematical algorithms for identifying the critical amount of intervention necessary to control infectious diseases and formulate intervention policies that minimize socio-economic cost.

2. JMD

   Optimization of Design Margins Allocation When Making Use of Additive Remanufacturing

   Al Handawi, Khalil, Panarotto, Massimo, Andersson, Petter, Isaksson, Ola, and Kokkolaras, Michael

   Journal of Mechanical Design 2021

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   Coping with changing requirements by means of introducing design margins may result in overdesign. In this paper, we present a design optimization method for minimizing overdesign by exploiting additive remanufacturing. Our problem formulation makes use of recently defined constituents of design margins: buffer and excess. The proposed method can be used to obtain a set of design decisions for different changing requirement scenarios. We demonstrate it using a turbine rear structure design problem where changes in the temperature loads are met by depositing different types of stiffeners on the outer casing. The results of the case study are visualized in a tradespace, which allows for comparison between sets of optimal, flexible, and robust designs. Results show that the optimized set of design decisions balances flexibility and robustness in a cost-effective manner.

2020

1. Optimization-driven set-based design for dynamic design requirements

   Al Handawi, Khalil

   2020
2. JMD

   Scalable Set-based Design Optimization and Remanufacturing for Meeting Changing Requirements

   Al Handawi, Khalil, Andersson, Petter, Panarotto, Massimo, Isaksson, Ola, and Kokkolaras, Michael

   Journal of Mechanical Design 2020

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   Design requirements are often uncertain in the early stages of product development. Set-based design (SBD) is a paradigm for exploring, and keeping under consideration, several alternatives so that commitment to a single design can be delayed until requirements are settled. In addition, requirements may change over the lifetime of a component or a system. Novel manufacturing technologies may enable designs to be remanufactured to meet changed requirements. By considering this capability during the (SBD) optimization process, solutions can be scaled to meet evolving requirements and customer specifications even after commitment. Such an ability can also support a circular economy paradigm based on the return of used or discarded components and systems to working condition. We propose a (SBD) methodology to obtain scalable optimal solutions that can satisfy changing requirements through remanufacturing. We first use design optimization and surrogate modeling to obtain parametric optimal designs. This set of parametric optimal designs is then reduced to scalable optimal designs by observing a set of transition rules for the manufacturing process used (additive or subtractive). The methodology is demonstrated by means of a structural aeroengine component that is remanufactured by direct energy deposition of a stiffener to meet higher loading requirements.

2019

1. ICED2019

   A lifecycle cost-driven system dynamics approach for considering additive re-manufacturing or repair in aero-engine component design

   Lawand, Lydia, Al Handawi, Khalil, Panarotto, Massimo, Andersson, Petter, Isaksson, Ola, and Kokkolaras, Michael

   In Proceedings of the International Conference on Engineering Design, ICED 2019

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   Aero-engine component design decisions should consider re-manufacturing and/or repair strategies and their impact on lifecycle cost. Existing design approaches do not account for alternative production technologies such as the use of additive manufacturing in life extension processes. This paper presents a modeling and optimization methodology for examining the impact of design decisions in the early development stage on component lifecycle cost during the in-service phase while considering the potential use of additive manufacturing in life extension strategies. Specifically, a system dynamics model is developed to assess different end-of-life scenarios. Finally, an optimization problem is formulated and solved to minimize lifecycle cost with respect to design variables related to remanufacturing.

2018

1. NordDesign

   Integrating additive manufacturing and repair strategies of aeroengine components in the computational multidisciplinary engineering design process

   Al Handawi, Khalil, Lawand, Lydia, Andersson, Petter, Brommesson, Rebecka, Isaksson, Ola, and Kokkolaras, Michael

   In Proceedings of NordDesign: Design in the Era of Digitalization, NordDesign 2018 2018

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   This paper presents a methodology for integrating failure and lifecycle analysis related to additive manufacturing in a computational multidisciplinary engineering design framework. The specific goal of this framework is to quantify the impact of component design decisions on system-level performance in order to assess alternative manufacturing, re-manufacturing and repair strategies from both technical and business perspectives. The ultimate objective of this research is to enable such considerations in the early product design phases, where sufficient degree of freedom exists to identify component design solutions that can facilitate and accommodate different manufacturing and repair techniques that impact the entire lifecycle. The developed methodology is demonstrated by means of a jet engine component where repair strategies are included as variables in the computational design process. Numerical results confirm that these strategies can be used to trade among design attributes such as lifecycle cost, weight, and performance.

2017

1. sensors

   Analytical Modeling Tool for Design of Hydrocarbon Sensitive Optical Fibers

   Al Handawi, Khalil, Vahdati, Nader, Shiryayev, Oleg, and Lawand, Lydia

   Sensors (Basel, Switzerland) 2017

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   Pipelines are the main transportation means for oil and gas products across large distances. Due to the severe conditions they operate in, they are regularly inspected using conventional Pipeline Inspection Gages (PIGs) for corrosion damage. The motivation for researching a real-time distributed monitoring solution arose to mitigate costs and provide a proactive indication of potential failures. Fiber optic sensors with polymer claddings provide a means of detecting contact with hydrocarbons. By coating the fibers with a layer of metal similar in composition to that of the parent pipeline, corrosion of this coating may be detected when the polymer cladding underneath is exposed to the surrounding hydrocarbons contained within the pipeline. A Refractive Index (RI) change occurs in the polymer cladding causing a loss in intensity of a traveling light pulse due to a reduction in the fiber’s modal capacity. Intensity losses may be detected using Optical Time Domain Reflectometry (OTDR) while pinpointing the spatial location of the contact via time delay calculations of the back-scattered pulses. This work presents a theoretical model for the above sensing solution to provide a design tool for the fiber optic cable in the context of hydrocarbon sensing following corrosion of an external metal coating. Results are verified against the experimental data published in the literature.

2. sensors

   Corrosivity sensor for exposed pipelines based on wireless energy transfer

   Lawand, Lydia, Shiryayev, Oleg, Al Handawi, Khalil, Vahdati, Nader, and Rostron, Paul

   Sensors (Switzerland) 2017

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   External corrosion was identified as one of the main causes of pipeline failures worldwide. A solution that addresses the issue of detecting and quantifying corrosivity of environment for application to existing exposed pipelines has been developed. It consists of a sensing array made of an assembly of thin strips of pipeline steel and a circuit that provides a visual sensor reading to the operator. The proposed sensor is passive and does not require a constant power supply. Circuit design was validated through simulations and lab experiments. Accelerated corrosion experiment was conducted to confirm the feasibility of the proposed corrosivity sensor design.

2016

1. SNB

   Strain based FBG sensor for real-time corrosion rate monitoring in pre-stressed structures

   Al Handawi, Khalil, Vahdati, Nader, Rostron, Paul, Lawand, Lydia, and Shiryayev, Oleg

   Sensors and Actuators, B: Chemical 2016

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   A strain based corrosion sensor for the detection of environmental corrosion of pre-stressed structures was developed and tested on mild steel specimens readily available. Theoretically, a beam shaped specimen under a displacement load exhibits a linear relationship between the strain observed at any point through the thickness of the beam cross-section. This property was exploited to detect thickness changes in pre-stressed mild steel specimens in a double bending configuration under an electrochemically excited corrosion reaction. The reaction was accelerated by supplying a DC current to the cell where the specimens act as anodes of the system, while graphite rods serve as cathodes. The strain was logged using fiber optic Bragg grating technology and conventional electrical strain gages simultaneously. Results show a strong relationship between the corrosion rate observed by back-calculation from supplied current and the time derivative of the measured strain values. Application of this sensor can therefore be extended to a variety of structures under mechanical loading, proving valuable for both its ability to measure corrosion rate in real-time, while maintaining an intrinsically safe nature appropriate by industrial standards.

2. SPIE2016

   Corrosivity monitoring system using RFID-based sensors

   Lawand, Lydia, Shiryayev, Oleg, Al Handawi, Khalil, Vahdati, Nader, and Rostron, Paul

   Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2016

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   In the oil and gas industry, pipeline integrity is a serious concern due to the consequences of pipeline failure. External corrosion was identified as one of the main causes of pipeline failures worldwide. A solution that addresses the issue of detecting and quantifying corrosivity of environment for application to existing exposed pipelines has been developed. The proposed sensor consists of an electric circuit and a sensing array connected to the circuit. The sensing array is an assembly of strips made of a metal identical to that of the pipe, having the same length and width, but different thicknesses. The sensing array is exposed to the same environment as the pipe. As corrosion propagates in the metal strips of the array, it corrodes the metal until it finally breaks the metal strip apart resulting in a discontinuity in the circuit. The sensor circuit is energized using electromagnetic field, and its function is to indicate which strips in the array are fully corroded. Visual indication is provided to the operator via LEDs. The proposed sensor can be installed on existing pipelines without altering the pipe structure or disturbing the production process. It is passive and has low maintenance requirements. Circuit design was validated through lab experiments. Results obtained from experiments were consistent with simulation results. \textcopyright (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

3. SPIE2016

   Corrosion monitoring along infrastructures using distributed fiber optic sensing

   Al Handawi, Khalil, Vahdati, Nader, Shiryayev, Oleg, and Lawand, Lydia

   Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2016 2016

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   Pipeline Inspection Gauges (PIGs) are used for internal corrosion inspection of oil pipelines every 3-5 years. However, between inspection intervals, rapid corrosion may occur, potentially resulting in major accidents. The motivation behind this research project was to develop a safe distributed corrosion sensor placed inside oil pipelines continuously monitoring corrosion. The intrinsically safe nature of light provided motivation for researching fiber optic sensors as a solution. The sensing fiber’s cladding features polymer plastic that is chemically sensitive to hydrocarbons within crude oil mixtures. A layer of metal, used in the oil pipeline’s construction, is deposited on the polymer cladding, which upon corrosion, exposes the cladding to surrounding hydrocarbons. The hydrocarbon’s interaction with the cladding locally increases the cladding’s refractive index in the radial direction. Light intensity of a traveling pulse is reduced due to local reduction in the modal capacity which is interrogated by Optical Time Domain Reflectometery. Backscattered light is captured in real-Time while using time delay to resolve location, allowing real-Time spatial monitoring of environmental internal corrosion within pipelines spanning large distances. Step index theoretical solutions were used to calculate the power loss due changes in the intensity profile. The power loss is translated into an attenuation coefficient characterizing the expected OTDR trace which was verified against similar experimental results from the literature. A laboratory scale experiment is being developed to assess the validity of the model and the practicality of the solution. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.