This thesis is directed towards the comparison of active and passive bolts systems to reveal which system shows the most favorable behavior for improved performance, safety and cost. This was achieved through the incorporation of new technologies, field data, numerical modeling and established theories in ground control analysis. All in all, a better understanding of the quasi-static behavior of underground coal mine roofs has been attained. Over the summer of 2010, the Department of Mining and Mineral Resource Engineering at Southern Illinois University Carbondale, in conjunction with Andy Hyett of YieldPoint Inc., Peabody and the National Institute of Occupational Safety and Health (NIOSH), installed over one hundred and seventy instrumented extensometers, closure meters, shear-meters, passive rebar roof bolts, tension rebar roof bolts, and double lock rebar roof bolts at three coal mines. Two of the three coal mines were room-and-pillar mines and the other a longwall mine. Data was routinely collected over a nine-month period to analyze shearing, dilation, and axial bolt loading occurring within the rock mass, and entry closure occurring between the excavation hanging-wall and foot-wall. Based on bolt loadings, shear, axial behavior and statistical analysis, initial results indicate that active roof bolts do not show superior performance for the added cost. Active bolts seem to show no difference from passive bolts in the initial loading phase either, indicating that tension bleed-off is a concern soon after installation; however, this observation was not captured, as the data loggers were not intrinsically safe. Considering the modeling results, the trends in axial loading seem to be calibrated but the magnitudes are not. Computer modeling also shows the potential to accurately model in situ bolt performance; however, challenges remain in obtaining a good match between numerical modeling and field observations.

Additive manufacturing (AM) is a growing section of the advanced manufacturing field and is being used to fabricate an increasing number of critical components, from aerospace components to medical implants. At the same time, cyber-physical attacks targeting manufacturing systems have continued to rise. For this reason, there is a need to research new techniques and methods to ensure the integrity of parts fabricated on AM systems. This work seeks to address this need by first performing a detailed analysis of vulnerabilities in the AM process chain and how these attack vectors could be used to execute malicious part sabotage attacks. This work demonstrated the ability of an internal void attack on the .STL file to reduce the yield load of a tensile specimen by 14% while escaping detection by operators. To mitigate these vulnerabilities, a new impedance-based approach for in situ monitoring of AM systems was created. Two techniques for implementing this approach were investigated, direct embedding of sensors in AM parts, and the use of an instrumented fixture as a build plate. The ability to detect changes in material as small as 1.38% of the printed volume (53.8 mm3) on a material jetting system was demonstrated. For metal laser powder bed fusion systems, a new method was created for representing side-channel meltpool emissions. This method reduces the quantity of data while remaining sensitive enough to detect changes to the toolpath and process parameters caused by malicious attacks. To enable the SCMS to validate part quality during fabrication required a way to receive baseline part quality information across an air-gap. To accomplish this a new process noise tolerant method of cyber-physical hashing for continuous data sets was presented. This method was coupled with new techniques for the storage, transmission, and reconstructing of the baseline quality data was implemented using stacks of "ghost" QR codes stored in the toolpath to transmit information through the laser position. A technique for storing and transmitting quality information in the toolpath files of parts using acoustic emissions was investigated. The ATTACH (additive toolpath transmission of acoustic cyber-physical hash) method used speed modulation of infill roads in a material extrusion system to generate acoustic tones containing quality information about the part. These modulations were able to be inserted without affecting the build time or requiring additional material and did not affect the quality of the part that contained them. Finally, a framework for the design and implementation of a SCMS for protecting AM systems against malicious cyber-physical part sabotage attacks was created. The IDEAS (Identify, Define, Establish, Aggregate, Secure) framework provides a detailed reference for engineers to use to secure AM systems by leveraging the previous work in vulnerability assessment, creation of new side-channel monitoring techniques, concisely representing quality data, and securely transmitting information to air-gapped systems through physical emissions. / Doctor of Philosophy / Additive manufacturing (AM), more widely known as 3D printing, is a growing field of manufacturing where parts are fabricated by building layers of material on top of each other. This layer-based approach allows the production of parts with complex shapes that cannot be made using more traditional approaches such as machining. This capability allows for great freedom in designing parts, but also means that defects can be created inside of parts during fabrication. This work investigates ways that an adversary might seek to sabotage AM parts through a cyber-physical attack. To prevent attacks seeking to sabotage AM parts several new approaches for security are presented. The first approach uses tiny vibrations to detect changes to part shape or material by attaching a small sensor either directly to the parts or to the surface that they are built on. Because an attack that sabotages an AM system (3D printer) could also affect the systems used to detect part defects these systems should be digitally separated from each other. By using a series of QR codes fabricated by the AM system along with the parts, information can be sent from the AM system to the monitoring system through its sensors. This prevents a cyber-attack from jumping from the AM system to the monitoring system. By temporarily turning off the laser power and tracking the movements of the guiding mirrors the QR code information can be sent to the monitoring system without having to actually print the QR code. The information stored in the QR code is compared to the emission generated when fabricating the parts and is used to detect if an attack has occurred since that would change the emissions from the part, but not from the QR code. Another approach for sending information from the AM system using physical emissions is by using sounds generated during part fabrication. Using a desktop scale 3D printer, the speed of certain movements was increased or decreased. The change in speed causes the sound emitted from the printer to change, while not affecting the actual quality of the print. By using a series of tones, similar to Morse code, information can be sent from the printer. Research was performed on the best settings to use to transmit the information as well as how to automatically receive and decode the information using a microphone. The final step in this work is a framework that serves as a guide for designing and implementing monitoring systems that can detect sabotage attacks on AM parts. The framework covers how to evaluate a system for potential vulnerabilities and how to use this information to choose sensors and data processing techniques to reduce the risk of cyber-physical attacks.

Additive friction stir deposition (AFSD) is an emerging solid-state metal additive manufacturing technology that uses deformation bonding to create near-net shape 3D components. As a developing technology, a deeper understanding of the processing science is necessary to establish the process-structure relationships and enable improved control of the as-printed microstructure and material properties. AFSD provides a unique opportunity to explore the friction stir fundamentals via direct observation of the material during processing. This work explores the relationship between the processing parameters (e.g., tool rotation rate Ω, tool velocity V, and material feed rate F) and the thermomechanical history of the material by process monitoring of i) the temperature evolution, ii) the force evolution, and iii) the interfacial contact state between the tool and deposited material. Empirical trends are established for the peak temperature with respect to the processing conditions for Cu and Al-Mg-Si, but a key difference is noted in the form of the power law relationship: Ω/V for Cu and Ω2/V for Al-Mg-Si. Similarly, the normal force Fz for both materials correlates to V and inversely with Ω. For Cu both parameters show comparable influence on the normal force, whereas Ω is more impactful than V for Al-Mg-Si. On the other hand, the torque Mz trends for Al-Mg-Si are consistent with the normal force trends, however for Cu there is no direct correlation between the processing parameters and the torque. These distinct relationships and thermomechanical histories are directly linked to the contact states observed during deformation monitoring of the two material systems. In Cu, the interfacial contact between the material and tool head is characterized by a full slipping condition (δ=1). In this case, interfacial friction is the dominant heat generation mechanism and compression is the primary deformation mechanism. In Al-Mg-Si, the interfacial contact is characterized by a partial slipping/sticking condition (0<δ<1), so both interfacial friction and plastic energy dissipation are important mechanisms for heat generation and material deformation. Finally, an investigation into the contact evolution at different processing parameters shows that the fraction of sticking is critically dependent on the processing parameters which has many implications on the thermomechanical processing history. / Doctor of Philosophy / Additive manufacturing or three-dimensional (3D) printing technologies have been lauded for their ability to fabricate complex geometries and multi-material parts with reduced material waste. Of particular interest is the use of metal additive manufacturing for repair and fabrication of industrial and structural components. This work focuses on characterizing the thermomechanical processing history for a developing technology Additive Friction Stir Deposition (AFSD). AFSD is solid-state additive manufacturing technology that uses frictional heat and mechanical mixing to fabricate 3D metal components. From a fundamental materials science perspective, it is imperative to understand the processing history of a material to be able to predict the performance and properties of a manufactured part. Through the use of infrared imaging, thermocouples, force sensors, and video monitoring this work is able to establish quantitative relationships between the equipment processing parameters and the processing history for Cu and Al. This work shows that there is a fundamental difference in how these two materials are processed during AFSD. In the future, these quantitative relationships can be used to validate modeling efforts and improve manufacturing quality of parts produced via friction stir techniques.

L’élaboration de multimatériaux en couches par métallurgie des poudres permet de réduire les coûts de fabrication, et d’augmenter les performances d’une pièce. Néanmoins, l’assemblage de multicouches engendre bien souvent des fissures ou même des délaminations, qui nuisent aux bonnes propriétés de la pièce. Ces travaux de thèse ont donc pour objectif de mieux comprendre quels peuvent être les paramètres importants à prendre en considération et leurs influences pour l’élaboration de multimatériaux. Pour cela, le cofrittage de trois couples de bimatériaux en couches massives a été étudié. Pour apprécier la cause de l’endommagement dans les bicouches, un dispositif de suivi in situ sans contact a été développé afin d’observer les déformations, les fissures, et les délaminations. De plus, la simulation du cofrittage grâce à un modèle de loi de comportement de type Binghamien a été réalisée dans le but de connaître le champ de contraintes résiduelles : les fissures observées ont été corrélées à ce champ de contraintes. Pour un premier couple de matériaux sans aucune interaction (Al2O3/ZrO2), il apparait nécessaire d’avoir des retraits qui débutent à des températures similaires, des retraits finaux proches, et une densification incomplète pour éviter l’endommagement. L’étude concernant la présence d’une phase liquide à l’interface (Al2O3/WC-Co) a souligné que celle-ci accroit l’accroche à l’interface pendant le frittage, mais qu’elle la fragilise lors du refroidissement. En présence d’une réaction à l’interface (ZrO2/Ti) une forte accroche chimique permet même de contrecarrer les effets néfastes d’un fort différentiel de retrait final. / The multilayer materials processed by powder metallurgy allow reducing the manufacturing cost. However, the multilayers assembly often leads to cracks or even debonding, which decreases the piece properties. The main purpose of this work is to better understand which important parameters have to be taken into account and their influences on the multimaterials processing. In order to fulfil this objective, the cosintering of three different couples of bimaterials in thick layer has been studied. To identify the damaging reasons in the bilayers, an in situ monitoring device has been developed to observe deformations, cracks and debonding. Moreover, the cosintering simulation with a Binghamien law model was performed to evaluate the internal stresses field : the experimentally observed cracks were correlated with this internal stresses field. For a first couple of materials with no interaction (Al2O3/ZrO2), it appears the necessity to have shrinkages which begin at similar temperatures, similar final shrinkages and an incomplete densification to avoid damaging. The study concerning the presence of a liquid phase at the interface (Al2O3/WC-Co) underlined that this liquid phase increases the bonding during the sintering, but decreases it during the cooling. With a reaction at the interface (ZrO2/Ti), a strong chemical bonding allows to avoid the bad effects of an important differential final shrinkage.

Selective laser melting (SLM) is a method of additive manufacturing that has become increasingly popular in recent years for fabricating complex components, especially in the medical and aerospace industries. By fabricating components in a layerwise fashion, SLM provides users the freedom to design components based on their desired functionality rather than their manufacturability. The current state-of-the-art for SLM is limited though, as defects induced by the SLM process have proven to greatly alter the material properties of fabricated parts. In addition, traditional post-process nondestructive inspection methods have experienced significant difficulty in accurately detecting these process-induced defects. Therefore, the objective of this study is to investigate methods of processing and analysis for optical in-situ monitoring data recorded during SLM fabrication of six test samples. Four of the samples were designed with seeded (i.e., intentional) defects located at their center to serve as a reference defect signatures in the resulting in-situ data. An off-axis optical tomography (OT) sensor was used to capture near-infrared (NIR) melt pool emissions during the fabrication of each layer. Image analysis was subsequently performed using a custom squared difference (SD) operator to enhance defect signatures in the OT data. Results from the SD operator were then used to perform k-means clustering to partition the data into k relevant clusters, where the optimal number of k clusters for each image is employed as metric for detecting the onset of defects in the samples. By employing OT image data from samples containing seeded intentional defects, the k-means clustering approach was investigated as a method of defect detection for the in-situ OT images. Results showed that the SD operator is capable of elucidating anomalous signatures in the in-situ data. However, variations within the SD distributions ultimately limited detection capabilities as the output from k-means clustering was unable to accurately distinguish the seeded defects from the fused regions of material.

No description available.

The world of additive manufacturing revolves around speed and repeatability. Inherently, the process of 3D printing is plagued with variability that fluctuates with every material and parameter modification. Without proper qualification standards, processes can never become stable enough to produce parts that may be used in aerospace, medical, and construction industries. These industries rely on high quality metrics in order to protect the lives of those who may benefit from them. To establish trust in a process, all points of variation must be controlled and accounted for every part produced. In instances where even the best process controls are enacted, there still may be situational unknowns that can cause detrimental defects, often on micron scales. Through in-situ monitoring techniques, such as visual or acoustic monitoring, a secondary level of quality assessment can be performed. This type of real time monitoring solution can be used in a variety of ways to help reduce scrap rate, increase overall quality, and improve the mechanical characteristics of a newly developing material. In this proposal, a goal was set to develop a system that can be a low-cost alternative to a comparable acoustic monitoring system. This design is meant to be a low fidelity concept that can alert a user of any potential anomalies within a build by detecting spikes in acoustic emissions. The overall success of this experiment is set on two conditions. First, the new low-cost system should be mountable on various types of machines. Second, this system should demonstrate some level of equivalency to a similar system. These two situations were successfully met as the system was able to provide indications of anomalies present within a build. The system was calibrated and tuned to be able to measure signals on a SLM 125 running 316L powder. Minor modifications to the code and system can make it adaptable to different types of equipment such as CNC’s, bandsaws, casting processes, and other advanced manufacturing equipment. The model can be attenuated to support higher or lower frequencies as well as different types of acoustic sensors, which demonstrates the vast potential that this system can provide for detecting different types of defects.

This thesis proposes a new method for detecting malicious cyber-physical attacks on additive manufacturing (AM) systems. The method makes use of a physical hash, which links digital data to the manufactured part via a disconnected side-channel measurement system. The disconnection ensures that if the network and/or AM system become compromised, the manufacturer can still rely on the measurement system for attack detection. The physical hash takes the form of a QR code that contains a hash string of the nominal process parameters and toolpath. It is manufactured alongside the original geometry for the measurement system to scan and compare to the readings from its sensor suite. By taking measurements in situ, the measurement system can detect in real-time if the part being manufactured matches the designer's specification. A proof-of-concept validation was realized on a material extrusion machine. The implementation was successful and demonstrated the ability of this method to detect the existence (and absence) of malicious attacks on both process parameters and the toolpath. A case study for detecting changes to the toolpath is also presented, which uses a simple measurement of how long each layer takes to build. Given benchmark readings from a 30x30 mm square layer created on a material extrusion system, several modifications were able to be detected. The machine's repeatability and measurement technique's accuracy resulted in the detection of a 1 mm internal void, a 2 mm scaling attack, and a 1 mm skewing attack. Additionally, for a short to moderate length build of an impeller model, it was possible to detect a 0.25 mm change in the fin base thickness. A second case study is also presented wherein dogbone tensile test coupons were manufactured on a material extrusion system at different extrusion temperatures. This process parameter is an example of a setting that can be maliciously modified and have an effect on the final part strength without the operator's knowledge. The performance characteristics (Young's modulus and maximum stress) were determined to be statistically different at different extrusion temperatures (235 and 270 °C). / Master of Science / Additive Manufacturing (AM, also known as 3D printing) machines are cyber-physical systems and are therefore vulnerable to malicious attacks that can cause physical damage to the parts being manufactured or even to the machine itself. This thesis proposes a new method for detecting that an AM system has been hacked. Attacks are identified via a series of measurements taken by a measurement system that is disconnected from the main network. The disconnection ensures that if the network and/or AM system are hacked, the manufacturer can still rely on the measurement system for attack detection. The proposed method uses a physical hash to transfer information to the disconnected measurement system. This physical hash takes the form of a QR code and stores in it the nominal process parameters and toolpath of the build. It is manufactured alongside the original geometry for the measurement system to scan and compare to the readings from its sensor suite. By taking measurements in real-time, the measurement system can detect if the part being manufactured matches the designer’s specification. A proof-of-concept of the proposed method was realized on a common AM system. The implementation was successful and demonstrated the ability of this method to detect the existence of a malicious attack. A case study for detecting changes to the toolpath is also proposed using the simple measurement of how long each layer takes to build. Given benchmark readings of a part manufactured on the same technology as the proof-of-concept implementation, several modifications were able to be detected. The attack types tested were the insertion of an internal void, scaling the part, and skewing the part. A second case study is also presented where components were manufactured at different extrusion temperatures. By measuring the force required to break the parts, it was determined that temperature has an effect on the final part strength. This confirmed that malicious attacks targeting extrusion temperature are a plausible threat, and that the parameter should be measured in the proposed system.

Yes / In a competitive coformer exchange reaction, a recent topic of interest in pharmaceutical research, the coformer in a pharmaceutical cocrystal is exchanged with another coformer which is expected to form a cocrystal that is more stable. There will be a competition between coformers to form the most stable product through formation of hydrogen bonds. Thus, to monitor each and every step of such reactions, employing a very sensitive technique is crucial. 1H nuclear magnetic resonance (NMR) is a very powerful technique that is very sensitive to the hydrogen bond interactions. In this study, an in situ monitoring of a coformer exchange reaction is carried out by 1H magic angle spinning (MAS) solid-state NMR (SSNMR) at a spinning frequency of 60 KHz. The changes in caffeine maleic acid cocrystals on addition of glutaric acid, and caffeine glutaric cocrystal on addition of maleic acid were monitored. In all the reactions, it has been observed that caffeine glutaric acid Form I is formed. When glutaric acid was added to 2:1 caffeine maleic acid, the formation of metastable 1:1 caffeine glutaric acid Form I was observed, at the start of the experiment, indicating that the centrifugal pressure is enough for the formation. The difference in the end product of the reactions with similar reaction pathway of 1:1 and 2:1 reactant stoichiometry indicate that a complete replacement of maleic acid has only occurred only in the 1:1 stoichiometry of the reactants. The polymorphic transition of caffeine glutaric acid Form II to Form I at higher temperature was crucial reason which triggers the exchange of glutaric acid with maleic acid in the reaction of caffeine glutaric acid and maleic acid. Based on these results, new reaction pathways in competitive coformer exchange reactions could be distinguished, and the remarkable role of stoichiometry, polymorphism, temperature and centrifugal pressure could be established. / C.H. acknowledges Department of Science and Technology, India (DST), for the grant of Inspire Fellowship. T.G.A. acknowledges Council of Scientific and Industrial Research, India (CSIR) for research grants under the 12th 5 year plan project (Grant No. CSC0405). / The full-text of this article will be released for public view at the end of the publisher embargo on 19 Feb 2025.

Analysis of the molecular speciation of organic compounds in solution is essential for the understanding of ionic complexation. The Raman spectroscopic technique was chosen for this purpose because it allows the identification of compounds in different states and it can give information about the molecular geometry from the analysis of the vibrational spectra. In this research the ionisation steps of relevant pharmaceutical material have been studied by means of potentiometry coupled with Raman spectroscopy; the protonation and deprotonation behaviour of the molecules were studied in different pH regions. The abundance of the different species in the Raman spectra of aqueous salicylic acid, paracetamol, citric acid and salicylaldoxime have been identified, characterised and confirmed by numerical treatment of the observed spectral data using a multiwavelength curve-fitting program. The non-destructive nature of the Raman spectroscopic technique and the success of the application of the multiwavelength curve-fitting program demonstrated in this work have offered a new dimension for the rapid identification and characterisation of pharmaceuticals in solution and have indicated the direction of further research. The work also covers the formation of novel cocrystal systems with pharmaceutically relevant materials. The existence of new cocrystals of salicylic acid-nicotinic acid, DLphenylalanine , 6-hydroxynicotinic acid, and 3,4-dihydroxybenzoic acid with oxalic acid have been identified from stoichiometric mixtures using combined techniques of Raman spectroscopy (dispersive and transmission TRS), X-ray powder diffraction and thermal analysis. Raman spectroscopy has been used to demonstrate a number of important aspects regarding the nature of the molecular interactions in the cocrystal. Cocrystals of salicylic acid - benzamide, citric acid-paracetamol and citric acid -benzamide have been identified with similar analytical approaches and structurally characterised in detail with single crystal X-ray diffraction. From these studies the high selectivity and direct micro sampling of Raman spectroscopy make it possible to identify spectral contributions from each chemical constituent by a peak wavenumber comparison of single-component spectra (API and guest individually) and the two- component sample material (API/guest), thus allowing a direct assessment of cocrystal formation to be made. Correlation of information from Raman spectra have been made to the X-ray diffraction and thermal analysis results. Transmission Raman Spectroscopy has been applied to the study cocrystals for the first time. Identification of new phases of analysis of the low wavenumber Raman bands is demonstrated to be a key advantage of the TRS technique.