Abstract: In the modern era of advanced technologies, rapid and accurate analyses are needed, both for scientific research and for industrial applications. For this reason, the Surface Plasmon Resonance (SPR) technology emerged as very successful particularly in the last ten years, being capable of measuring interactions in real time with high sensitivity and without the need for labels. Thanks to these characteristics, SPR has gained great popularity and represents a viable choice for many applications, from life sciences to pharmaceutics, agrifood and environmental monitoring of harmful substances. Herein, we examine the recent advances in the development of SPR technology to provide an excursus on the various types of instrumentation available on the market, discuss their advantages and their limitations as well as future trends, and to analyze particular case studies addressed by SPR technology.

Abstract: Non-target screening (NTS) methods are rapidly gaining in popularity, empowering researchers to search for an ever-increasing number of chemicals. Given this possibility, communicating the confidence of identification in an automated, concise and unambiguous manner is becoming increasingly important. In this study, we compiled several pieces of evidence necessary for communicating NTS identification confidence and developed a machine learning approach for classification of the identifications as reliable and unreliable. The machine learning approach was trained using data generated by four laboratories equipped with different instrumentation. The model discarded substances with insufficient identification evidence efficiently, while revealing the relevance of different parameters for identification. Based on these results, a harmonized IP-based system is proposed. This new NTS-oriented system is compatible with the currently widely used five level system. It increases the precision in reporting and the reproducibility of current approaches via the inclusion of evidence scores, while being suitable for automation.

Abstract: Solar-powered systems require real-time monitoring because the rapid environmental change affects the system with no specifics when such occurrences will happen. The systems rely solely on the amount of solar irradiance, which can affect the overall working performance. This paper introduces cost-effective instrumentation and measurement of the entire solar system essential for remote areas. The instrumentation method described in this paper offers a low-cost method for real-time monitoring of the voltage of the battery bank, current from the PV, AC from the converter and oil well control. An Arduino board serves as the foundation for the system design. A low-cost current, voltage and float switch sensors are used for the acquisition, and data are presented in Excel using the PLX-DAQ data acquisition Excel Macro, which enables the communication between the Arduino U.N.O. board's ATMega328 microcontroller and the computer via the UART bus.

Abstract: With the growing number of well-aged bridges and the urgency in developing reliable, (pseudo-) real-time monitoring of structural safety and integrity, there is a worldwide and widespread campaign toward transforming structural health monitoring practice. Among these attempts, the application of data-driven approaches in developing damage identification techniques has received particular attention in recent years. Given the growing volume of structural health monitoring data, the power of data-driven approaches has been further exploited. These efforts have been predominantly focused on building and training algorithms using direct measurements from bridges. Although recent years have seen transformative technologies in producing cheap and wireless sensors, network-wide bridge instrumentation is logistically difficult and expensive. This has led to a new group of structural health monitoring systems entitled indirect or drive-by approaches. In drive-by systems, measurements from an instrumented vehicle are used to extract structural damage signatures. In other words, in these systems, the instrumented vehicle acts as both actuator and receiver while passing over a bridge. The main challenge in deploying drive-by approaches for damage identification purposes is that the signals collected on drive-by vehicles also embody signatures from the vehicle, road/rail profile and are easily contaminated by environmental and operational conditions. Furthermore, the majority of current drive-by damage identification systems rely on prior knowledge of vehicle or bridge dynamic characteristics which has led to limited application of the concept in practice so far. To address these challenges, this study employs a powerful class of deep learning algorithm to develop a damage identification system using measurements on an instrumented travelling train. The proposed algorithm is capable of automatically extracting damage signatures from train-borne measurements only. To demonstrate the algorithm’s capability, the method is applied to measurements collected on a model instrumented train travelling on a simply supported model steel bridge. For this purpose, a deep convolutional neural network is built, optimised, trained and tested to detect damage using acceleration signals collected on the instrumented train only. The hyperparameters of the algorithm are optimised using the Bayesian optimisation technique. The accuracy of the algorithm is experimentally tested for four positive damage scenarios (combination of two different locations and intensity) and three different travelling speeds. This is the first demonstration of the data-driven drive-by damage identification system under scaled operational environment conditions. The performance of the proposed method is discussed under different travelling speeds and different damage states. The result shows that the proposed method can accurately and automatically detect and classify damage under varying speed, rail irregularities and operational noise using train-borne measurements only and offers a great promise in transforming the future of bridge damage identification system.

Abstract: Recent advances in artificial intelligence (AI) and data analytics (DA) could provide opportunities for the fault management and the decision-making of the urban wastewater treatment systems (UWS) operations. The UWS is typically a large system, including Sewer networks (SNs), Wastewater Treatment plants (WWTPs) and also considering the Receiving media (RM). However, applications of AI and DA in the UWS can be challenging due to the complexities and size of systems, the large variation in the level of UWS instrumentation, and the relatively poor data quality. This review goes beyond the state of the art by critically analyzing previous work on AI-based data-driven methodologies to system-wide fault detection, life cycle fault management and transformation of big and small data into analytics, particularly, considering two different points of view: process faults (such as bulking sludge, sewer corrosion & technology specifics) and instrumentation faults (such as sensors and actuators), thereby offering more opportunities to distinguish complex patterns and dynamics. Our analysis reveals the relative strengths and weaknesses of the different approaches to design fault diagnosis tools and to apply these in the UWS. Finally, the opportunities and challenges about the inter-play among UWS, data and AI are discussed.

Abstract: The focused ion beam (FIB) is a powerful tool for fabrication, modification, and characterization of materials down to the nanoscale. Starting with the gallium FIB, which was originally intended for photomask repair in the semiconductor industry, there are now many different types of FIB that are commercially available. These instruments use a range of ion species and are applied broadly in materials science, physics, chemistry, biology, medicine, and even archaeology. The goal of this roadmap is to provide an overview of FIB instrumentation, theory, techniques, and applications. By viewing FIB developments through the lens of various research communities, we aim to identify future pathways for ion source and instrumentation development, as well as emerging applications and opportunities for improved understanding of the complex interplay of ion–solid interactions. We intend to provide a guide for all scientists in the field that identifies common research interest and will support future fruitful interactions connecting tool development, experiment, and theory. While a comprehensive overview of the field is sought, it is not possible to cover all research related to FIB technologies in detail. We give examples of specific projects within the broader context, referencing original works and previous review articles throughout.

Abstract: Ice thickness is a critical parameter in single particle cryo-EM – too thin ice can break during imaging or exclude the sample of interest, while ice that is too thick contributes to more inelastic scattering that precludes obtaining high resolution reconstructions. Here we present the practical effects of ice thickness on resolution, and the influence of energy filters, accelerating voltage, or detector mode. We collected apoferritin data with a wide range of ice thicknesses on three microscopes with different instrumentation and settings. We show that on a 300 kV microscope, using a 20 eV energy filter slit has a greater effect on improving resolution in thicker ice; that operating at 300 kV instead of 200 kV accelerating voltage provides significant resolution improvements at an ice thickness above 150 nm; and that on a 200 kV microscope using a detector operating in super resolution mode enables good reconstructions for up to 200 nm ice thickness, while collecting in counting instead of linear mode leads to improvements in resolution for ice of 50–150 nm thickness. Our findings can serve as a guide for users seeking to optimize data collection or sample preparation routines for both single particle and in situ cryo-EM. We note that most in situ data collection is done on samples in a range of ice thickness above 150 nm so these results may be especially relevant to that community.

Abstract: The development life cycle of conventional nuclear power plants (NPPs) needs to be optimized if the energy produced by advanced reactors and small modular reactors is to be competitive. One of the proposed optimisation initiatives is the digitalization of nuclear facility control and instrumentation. Digitalization of nuclear control and instrumentation will improve plants' performance and cost competitiveness. However, it could also introduce cyber security challenges. To create a strong cyber-defence for critical digital assets in nuclear facilities, an extensive analysis of threats and vulnerabilities in systems, networks, and devices is necessary. This article examines recent research that analyses the digital assets at nuclear power facilities for threats and vulnerabilities. This work synthesizes and categorises potential attack propagation paths in digitalized nuclear facilities based on five different surfaces: direct network path, programmable logic controllers, sensor/actuator signals, and indirect propagation paths such as attacks that exploit human factors and the supply chain. The work's main contribution is it provides a state-of-the-art understanding of the relationship between attack propagation paths, associated vulnerabilities, and current security controls. Based on the literature review, a framework for developing an attack-resilient control system for NPPs is suggested, which would be helpful for a security-informed design of reactor control systems. The discussion on nuclear cyber risks, vulnerabilities, attack routes, and defence methods offers a cutting-edge understanding of the security challenges in digitalized nuclear facilities. The suggested framework is an essential foundation for future research direction, towards a secured and resilient digitisation of nuclear power plant control systems.

Abstract: Abstract Coherent Raman scattering (CRS) microscopy is a chemical imaging modality that provides contrast based on intrinsic biomolecular vibrations. To date, endeavors on instrumentation have advanced CRS into a powerful analytical tool for studies of cell functions and in situ clinical diagnosis. Nevertheless, the small cross-section of Raman scattering sets up a physical boundary for the design space of a CRS system, which trades off speed, signal fidelity and spectral bandwidth. The synergistic combination of instrumentation and computational approaches offers a way to break the trade-off. In this review, we first introduce coherent Raman scattering and recent instrumentation developments, then discuss current computational CRS imaging methods, including compressive micro-spectroscopy, computational volumetric imaging, as well as machine learning algorithms that improve system performance and decipher chemical information. We foresee a constant permeation of computational concepts and algorithms to push the capability boundary of CRS microscopy.

Abstract: Due to significant advances in instrumentation, many previously specialized techniques have become “routine” in user facilities. However, detailed knowledge held by experts has often not been relayed to general users, so they often rely on entry-level information, basic principles, and comparison with literature results for data analysis. As a result, major errors in the data analysis of multiple surface and material analysis techniques, including in x-ray photoelectron spectroscopy (XPS), have been appearing in the scientific literature. Representative examples of serious errors in XPS data analysis are shown in this work. We suggest that surface and material analysis, and perhaps even science in general, are in a state of “pre-crisis.” We use two (logistic) models from population biology to suggest that bad analyses self-correct if they remain below a critical number. However, beyond a threshold, the literature can become useless because of the perpetuation of faulty analyses and concomitant loss of its self-correcting ability. XPS is used by scientists in many communities because of the power of the technique and high-quality instrumentation that is commercially available. Those who make new surfaces and materials face unique challenges because of the large number of surface and material analytical techniques that are often needed to characterize their materials. Graduate students and post-docs are often provided with only minimal instruction on using surface and material characterization methods. High fees for instruments may affect both the quality and the quantity of the data people collect. The Prisoner's Dilemma is a model from game theory that describes situations with reward structures that encourage uncooperative behavior and lead to suboptimal outcomes. However, the outcomes of Prisoner's Dilemma are not inevitable—their consequences change if their reward structures change. The current system does not appear to incentivize detailed learning of surface and material characterization techniques and careful material characterization. Prisoner's dilemmas appear to lead to other undesirable consequences in science. The concerns raised in this work suggest that many manuscripts are incompletely reviewed at present. The different stakeholders in this problem, including authors, research advisers, subject matter experts, reviewers, scientists who notice examples of faulty data analysis, editors, journals and publishers, funding agencies, scientific societies, leaders at universities and research centers, and instrument vendors, can improve the current situation. This work provides specific recommendations for each of these stakeholders. For example, we believe that authors are primarily responsible for the correctness of their work, not reviewers or editors; we question the wisdom of listing the names of the editor and reviewers on a paper; we are grateful for the significant contributions that have been made by subject matter experts to produce standards and tutorial information; the high cost of instrument time at some institutions may limit student access and result in suboptimal analyses; staff scientists often need to be better recognized for their intellectual contributions to studies; publishers may wish to allow selective reviewing of specific sections of papers related to material characterization; the reviewing at some open access journals may be inadequate; while it had its shortcomings, the pre-open access model of publishing incentivized the production and publication of high-quality work; audits of the products (scientific papers) of funding agencies may be necessary; collaboration needs to be encouraged to a greater extent at some institutions; and instrument vendors should not suggest to potential customers that surface characterization, e.g., by XPS, is trivial or simple.

Abstract: As data science and instrumentation become key practices in common careers ranging from medicine to agriscience, chemistry as a core introductory course must introduce such topics to students early and at an accessible level. Advanced data acquisition and data science generally require expensive precision instrumentation and massive computation, often out-of-reach even for upper-level undergraduate laboratory courses. At the same time, a new generation of affordable do-it-yourself instruments presents an opportunity for incorporation of curricula focused on instrument design and computation into freshman-level courses. We present a new lab for integration into existing courses that starts with hands-on spectrometer building, moves to data collection, and finally introduces an advanced data science technique, singular value decomposition, at an appropriate level with minimal computing requirements. The hardware and software used are modular and inexpensive. The lab was tested in three community college general chemistry sections over two semesters. Previously, students taking these courses did not typically see advanced quantitative chemistry curricula before deciding whether to pursue a bachelor’s degree. This lab allowed students to practice data collection and organization skills, use prewritten Jupyter notebooks that perform advanced data analysis, and gain presentation skills. A multiwave assessment completed by students highlights both successes and difficulties associated with incorporating multiple advanced topics involving instrument design, data collection, and analysis techniques in a single lab.

Abstract: Many factors are considered when inspecting and evaluating the overall condition of a bridge. Of particular consideration here is load testing of bridges to evaluate the existing load-carrying capacity. Sensor systems are often mounted directly to girders for this assessment; however, installing sensors and data acquisition systems can be an expensive and time-consuming process, particularly given that load testing does not warrant long-term monitoring. As an alternative, noncontact remote sensing techniques have been developed for measuring structural deformations, and have the potential to be used for static load test applications. These approaches do not require sophisticated instrumentation installations, and can provide a denser array of measurements, compared with conventional sensors. A particular focus has been on techniques that use video recordings, tracking the motion between subsequent video frames via computer vision methods. There are now commercial offerings for such measurement systems, as well as an array of techniques that can be used for custom applications. While such methods have seen significant testing under laboratory conditions, there are only a limited number of studies that provide comparative methodological analyses under full-scale field conditions. This paper presents a case study on the use of vision-based methods for bridge load testing, and provides a comparison of a digital image correlation (DIC) approach with a phase-based optical flow method. Two sets of field experiments were performed on bridges in the state of Delaware. The results show that vision-based methods can provide comparable results to conventional sensor installations, given sufficient consideration of the unique technical demands of these methods, as well as operational logistics. In most cases, the DIC and phase-based methods provided comparable results, though the DIC system yielded generally better accuracy, owing to a combination of algorithmic differences and additional signal postprocessing.

Abstract: Bridges hold an imperative role in the transportation network and infrastructure. Continuous monitoring of their condition is crucial for the efficient operation of transportation facilities. Conventional bridge monitoring has relied on direct sensor instrumentation on the bridge to obtain the bridge response. Indirect bridge health monitoring (iBHM) leverages the moving traffic over the specific bridge of interest. The benefit of iBHM lies in the fact that bridge instrumentation is no longer required since the moving vehicle is instrumented with sensors. The collected data can be used to identify the dynamic characteristics of the bridge. Additionally, the method can be used to detect damage using the information of the vehicle bridge interaction. This paper systematically reviews the recent research progress in iBHM, and the review is organized based on four main groups, namely single test vehicles, tractor-trailer vehicles, crowdsourced/smartphone monitoring, and contact point (CP) response. The primary classification is further divided according to the nature of the investigation, which includes theoretical and numerical investigations, laboratory tests, and full-scale validations. After a concise and systematic review, the existing challenges and future recommendations are outlined. It is anticipated that this review will provide valuable guidance for researchers and practitioners of bridge engineering to understand better the evolution, development, and future trends of iBHM.

Abstract: LISA is a space-based mHz gravitational-wave observatory, with a planned launch in 2034. It is expected to be the first detector of its kind, and will present unique challenges in instrumentation and data analysis. An accurate preflight simulation of LISA data is a vital part of the development of both the instrument and the analysis methods. The simulation must include a detailed model of the full measurement and analysis chain, capturing the main features that affect the instrument performance and processing algorithms. Here, we propose a new model that includes, for the first time, proper relativistic treatment of reference frames with realistic orbits, a model for onboard clocks and clock synchronization measurements, proper modeling of total laser frequencies (including laser locking), frequency planning and Doppler shifts, better treatment of onboard processing, and updated noise models. We then introduce two implementations of this model, lisanode and lisa instrument. We demonstrate that TDI processing successfully recovers gravitational-wave signals from the significantly more realistic and complex simulated data. lisanode and lisa instrument are already widely used by the LISA community and, for example, currently provide the mock data for the LISA data challenges.

Abstract: High-risk human papillomavirus (HPV) DNA testing is widely acknowledged as the most sensitive cervical cancer screening method but has limited availability in resource-limited settings, where the burden of cervical cancer is highest. Recently, HPV DNA tests have been developed for use in resource-limited settings, but they remain too costly for widespread use and require instruments that are often limited to centralized laboratories. To help meet the global need for low-cost cervical cancer screening, we developed a prototype, sample-to-answer, point-of-care test for HPV16 and HPV18 DNA. Our test relies on isothermal DNA amplification and lateral flow detection, two technologies that reduce the need for complex instrumentation. We integrated all test components into a low-cost, manufacturable platform, and performance of the integrated test was evaluated with synthetic samples, provider-collected clinical samples in a high-resource setting in the United States, and self-collected clinical samples in a low-resource setting in Mozambique. We demonstrated a clinically relevant limit of detection of 1000 HPV16 or HPV18 DNA copies per test. The test requires six user steps, yields results in 45 min, and can be performed using a benchtop instrument and minicentrifuge by minimally trained personnel. The projected per-test cost is <$5, and the projected instrumentation cost is <$1000. These results show the feasibility of a sample-to-answer, point-of-care HPV DNA test. With the inclusion of other HPV types, this test has the potential to fill a critical gap for decentralized and globally accessible cervical cancer screening. Description We developed an HPV16 and HPV18 test and demonstrated its potential for cervical cancer screening in low-resource settings. Editor’s summary DNA-based screening methods for high-risk human papillomavirus (HPV) have proven to be highly effective for early cervical cancer detection but remain too expensive and difficult to use in resource-limited settings. Kundrod et al. developed a prototype, sample-to-answer, point-of-care test for detecting HPV16 and HPV18. This test uses isothermal DNA amplification and lateral flow detection with low-cost components that can detect HPV DNA at a clinically relevant limit of detection. This test was successfully demonstrated in a high-resource setting in the United States and in a low-resource setting in Mozambique, and it could be performed by minimally trained personnel at an estimated cost of <$5 per test. These results suggest that a sample-to-answer, point-of-care HPV DNA test is viable for low-resource settings and could improve access to cervical cancer screening. —Christiana Fogg

Abstract: The field of analytical chemistry has been significantly advanced by the availability of state-of-the-art instrumentation, allowing for the development of novel applications in this field. However, in many cases, the direct interpretation of the recorded data is often not straightforward, hence some level of pre-processing is required (e.g., baseline correction, derivatives, normalization, smoothing). These techniques have become a critical first step for the successful analysis of the data recorded, and it is recommended to use them before the application of chemometrics (e.g., classification, calibration development). The aim of this paper is to provide with an overview of the most used pre-processing methods applied to instrumental analytical methods (e.g., spectroscopy, chromatography). Examples of their application in near infrared and UV-VIS spectroscopy as well as in gas chromatography will be also discussed. Overall, this paper provides with a comprehensive understanding of pre-processing techniques in analytical chemistry, highlighting their importance during the analysis and interpretation of data, as well as during the development of accurate and reliable chemometric models.

Abstract: ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTSmall Molecule Probes for 19F Magnetic Resonance ImagingAo LiAo LiThe MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Fujian Provincial Key Laboratory of Chemical Biology, and Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen361005, ChinaMore by Ao LiView Biography, Xiangjie LuoXiangjie LuoThe MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Fujian Provincial Key Laboratory of Chemical Biology, and Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen361005, ChinaMore by Xiangjie LuoView Biography, Dongxia ChenDongxia ChenThe MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Fujian Provincial Key Laboratory of Chemical Biology, and Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen361005, ChinaMore by Dongxia ChenView Biography, Lingxuan LiLingxuan LiThe MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Fujian Provincial Key Laboratory of Chemical Biology, and Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen361005, ChinaMore by Lingxuan LiView Biography, Hongyu Lin*Hongyu LinThe MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Fujian Provincial Key Laboratory of Chemical Biology, and Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen361005, China*[email protected]More by Hongyu LinView Biographyhttps://orcid.org/0000-0002-5675-8537, and Jinhao Gao*Jinhao GaoThe MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Fujian Provincial Key Laboratory of Chemical Biology, and Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen361005, China*[email protected]More by Jinhao GaoView Biographyhttps://orcid.org/0000-0003-3215-7013Cite this: Anal. Chem. 2023, 95, 1, 70–82Publication Date (Web):January 10, 2023Publication History Received14 October 2022Published online10 January 2023Published inissue 10 January 2023https://doi.org/10.1021/acs.analchem.2c04539Copyright © 2023 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views549Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit Read OnlinePDF (7 MB) Get e-AlertscloseSUBJECTS:Ions,Magnetic resonance imaging,Probes,Sensor probes,Small molecules Get e-Alerts

Abstract: The S3-level clinical guidelines for the treatment of patients with periodontitis stages I-III published by the European Federation of Periodontology in 2020, suggest a pre-established stepwise approach for oral-healthcare professionals with precise therapeutic pathways. The second step of this approach consists of the subgingival instrumentation of periodontal pockets by non-surgical means to disrupt the microbial biofilm and remove soft and mineralized deposits This step aims to resolve periodontal inflammation by closure of periodontal pockets (probing pocket depth ≤ 4 mm, absence of bleeding on probing) employing different types of instruments and treatment protocols toward this end. Novel non-surgical treatment approaches that adopt micro instruments or subgingival application of biological agents have been recently tested. Subgingival instrumentation has been shown to effectively restore the subgingival microbiota to one associated with periodontal health and to modulate the inflammatory response. The outcomes of the subgingival instrumentation have to be evaluated in order to guide the therapist in providing additional but focused treatment in the remaining pockets OR at sites with residual inflammation. Of great importance is the impact that non-surgical periodontal treatment has on the patient's well-being, based on evidence that emerges from studies evaluating patient related outcomes and quality of life.

Abstract: On February 18th, 2021, the Mars 2020 entry system successfully delivered the Perseverance rover to the surface of Mars at Jezero Crater. The entry capsule carried a set of instrumentation installed on the heat shield and backshell, named the “Mars Entry, Descent, and Landing Instrumentation 2.” The instruments include pressure transducers, thermocouples, heat flux gauges, and radiometers to measure the aerodynamic and aerothermodynamic performance of the entry vehicle. This paper describes the trajectory and atmosphere reconstruction results based on the pressure sensor measurements. The process uses a Kalman filter approach to estimate the freestream atmospheric properties from the pressure measurements combined with a model of the pressure distribution of the heatshield and other sensor inputs, including an inertial measurement unit and other on-board navigation sensors, and several external atmospheric observations. The results indicate that the upper altitude density was up to 150% higher than nominal, which is consistent with the observed early entry guidance start time. The density below 40 km was within 12% of the preflight predictions. The reconstructed axial force coefficient was approximately 2% lower than the preflight prediction across the flight range.

Abstract: High-resolution distributed reinforcement strain measurements can provide invaluable information for developing and evaluating numerical and analytical models of reinforced concrete structures. A recent testing campaign conducted at UCLouvain in Belgium used fiber-optic sensors embedded along several longitudinal steel rebars of three reinforced concrete U-shaped walls. The resulting experimental dataset provides an opportunity to evaluate and compare, for different types of loading, the strain measurements obtained with the fiber-optic sensors in the confined core of the structural member against more conventional and state-of-the-practice sensors that monitor surface displacements and deformations. This work highlights the need to average strain measurements from digital image correlation techniques in order to obtain coherent results with the strains measured from fiber optics, and investigates proposals to achieve this relevant goal for research and engineering practices. The longitudinal strains measured by the fiber optics also provide additional detailed information on the behavior of these wall units compared to the more conventional instrumentation, such as strain penetration into the foundation and head of the wall units, which are studied in detail.