A modelling approach for predicting marine engines shaft dynamics

For making decisions on maintenance and operations of ship systems in a timely and cost effective way, intelligent approaches for continuously assessing the critical ship systems condition are required. This study aims to provide a framework for large marine two-stroke diesel engines performance assessment, by mapping the relationship of specific malfunctioning engine conditions on the Instantaneous Crankshaft Torque (ICT). This is accomplished by the development of a thermodynamics model, which is coupled with a lumped mass crankshaft dynamics model, in order to predict the engine shaft dynamics and torsional response. Subsequently, by employing the coupled engine models, a number of case studies are simulated for investigating the influence on the engine ICT, which include: (a) change in the Start of Injection (SOI), (b) change in the Rate of Heat Release (RHR), (c) change in the scavenge air pressure, and (d) leaking exhaust valve. By investigating the predicted ICT from the coupled model in both the time and frequency domains, distinct frequencies are identified, which correspond to specific engine malfunctioning conditions. Based on the derived results, these engine malfunctioning conditions are mapped with the frequencies most affected in the engine’s instantaneous torque, which demonstrate the usefulness of implementing the the ICT measurement for diagnostic purposes

A novel systematic methodology for ship propulsion engines energy management

Establishing an energy monitoring and management methodology is a quintessential milestone for informed energy savings decision making as well as for effectively reducing the cost and the environmental impact of shipping operations. In this study, a novel systematic methodology is proposed for the energy management of the ship propulsion engine, which is the largest ship energy producer. The methodology employs a combination of tools including statistical analysis, predicting the engine air flow via compressor modelling and energy and exergy analyses, whereas its output includes the engine operating profile, the most frequently occurring propeller curves and the engine most frequent operating points, the key performance indicators for quantitatively assessing the recorded parameters quality as well as the energy and exergy flows and exergy destruction of the engine components. The methodology is implemented for three case studies for a very large crude carrier, a container ship and a bulk carrier, for which recorded data were available by using different monitoring techniques from either noon reports of automatic data acquisition systems. The derived results provide the engine operating profile demonstrating that the investigated vessels were operating in slow steaming conditions with a lower engine efficiency associated with a greater exhaust gas wasted energy. The measured data analysis demonstrates the better quality of the data recorded by automated monitoring systems and pinpoint maintenance issues of the engine components. Lastly, the exergy analysis results demonstrate that the exhaust gas and jacket cooling water provide the greater exergy flows rendering them attractive for energy saving initiatives, whereas the engine block, compressor and turbine are the engine components with the greater exergy destruction, thus requiring closing monitoring for timely identifying mitigating measures

Systematic investigation of a large two-stroke engine crankshaft dynamics model

The crankshaft dynamics model is of vital importance to a multitude of aspects on engine diagnostics; however, systematic investigations of such models performance (especially for large two-stroke diesel engines that are widely used in the power generation and shipping industries) have not been reported in the literature. This study aims to cover this gap by systematically investigating the parameters that affect the performance of a two-stroke diesel engine crankshaft dynamics model, such as the numerical scheme as well as the engine components inertia and friction. Specifically, the following alternatives are analysed: (a) two optimal performing numerical schemes, in particular, a stiff ordinary differential equations (ODE) solver and a fast solver based on a piecewise Linear Time-Invariant (LTI) scheme method, (b) the linear and the non-linear inertia-speed approaches, and (c) three engine friction submodels of varying complexity. All the potential combinations of the alternatives are investigated, and the crankshaft dynamics model performance is evaluated by employing Key Performance Indicators (KPIs), which consider the results accuracy compared to the measured data, the computational time, and the energy balance error. The results demonstrate that the best performing combination includes the stiff ODE solver, the constant inertia-speed approach and the most simplistic engine friction submodel. However, the LTI numerical scheme is recommended for applications that require fast response due to the significant savings in computational time with an acceptable compromise in the model results accuracy

Early pH Changes in Musculoskeletal Tissues upon Injury-Aerobic Catabolic Pathway Activity Linked to Inter-Individual Differences in Local pH

Local pH is stated to acidify after bone fracture. However, the time course and degree of acidification remain unknown. Whether the acidification pattern within a fracture hematoma is applicable to adjacent muscle hematoma or is exclusive to this regenerative tissue has not been studied to date. Thus, in this study, we aimed to unravel the extent and pattern of acidification in vivo during the early phase post musculoskeletal injury. Local pH changes after fracture and muscle trauma were measured simultaneously in two pre-clinical animal models (sheep/rats) immediately after and up to 48 h post injury. The rat fracture hematoma was further analyzed histologically and metabolomically. In vivo pH measurements in bone and muscle hematoma revealed a local acidification in both animal models, yielding mean pH values in rats of 6.69 and 6.89, with pronounced intra- and inter-individual differences. The metabolomic analysis of the hematomas indicated a link between reduction in tricarboxylic acid cycle activity and pH, thus, metabolic activity within the injured tissues could be causative for the different pH values. The significant acidification within the early musculoskeletal hematoma could enable the employment of the pH for novel, sought-after treatments that allow for spatially and temporally controlled drug release

Engine malfunctioning conditions identification through instantaneous crankshaft torque measurement analysis

In this study a coupled thermodynamics and crankshaft dynamics model of a large two-stroke diesel engine was utilised, to map the relationship of the engine Instantaneous Crankshaft Torque (ICT) with the following frequently occurring malfunctioning conditions: (a) change in Start of Injection (SOI), (b) change in Rate of Heat Release (RHR), (c) change in scavenge air pressure, and (d) blowby. This was performed using frequency analysis on the engine ICT, which was obtained through a series of parametric runs of the coupled engine model, under the various malfunctioning and healthy operating conditions. This process demonstrated that engine ICT can be successfully utilised to identify the distinct effects of malfunctions (c) or (d), as they occur individually in any cylinder. Furthermore by using the same process, malfunctions (a) and (b) can be identified as they occur individually for any cylinder, however there is no distinct effect on the engine ICT among these malfunctions, since their effect on the in-cylinder pressure is similar. As a result, this study demonstrates the usefulness of the engine ICT as a non-intrusive diagnostic measurement, as well as the benefits of malfunctioning conditions mapping, which allows for quick and less resource intensive identification of engine malfunctions

Retrospective analysis of treatment decisions and clinical outcome of Lisfranc injuries: operative vs. conservative treatment

Purpose: Lisfranc injuries are rare and often pose a challenge for surgeons, particularly in initially missed or neglected cases. The evidence on which subtypes of Lisfranc injuries are suitable for conservative treatment or should undergo surgery is low. The aim of this study was to retrospectively analyze treatment decisions of Lisfranc injuries and the clinical outcome of these patients within the last ten years. Methods: All patients treated due to a Lisfranc injury in a German level I trauma centre from January 2011 until December 2020 were included in this study. Radiologic images and medical data from the patient files were analyzed concerning the classification of injury, specific radiologic variables, such as the Buehren criteria, patient baseline characteristics, and patient outcome reported with the Foot Function Index (FFI). Results: Ninety-nine patients were included in this study (conservative = 20, operative = 79). The overall clinical outcome assessed by the FFI was good (FFI sum 23.93, SD 24.93); patients that were identified as suitable for conservative treatment did not show inferior functional results. Qualitative radiological factors like the grade of displacement and the trauma mechanism were more strongly associated with the decision for surgical treatment than quantitative radiologic factors such as the distance from the first to the second metatarsal bone. Conclusion: If the indication for conservative or operative treatment of Lisfranc injuries is determined correctly, the clinical outcome can be comparable. These decisions should be based on several factors including quantitative and qualitative radiologic criteria, as well as the trauma mechanism

Clinical and Patient-Related Outcome After Stabilization of Dorsal Pelvic Ring Fractures: A Retrospective Study Comparing Transiliac Fixator (TIFI) and Spinopelvic Fixation (SPF)

Purpose: Aim of this retrospective cohort study was the comparison of the transiliac fixator (TIFI) and spinopelvic fixation (SPF) for fixation of dorsal pelvic ring fractures in terms of clinical outcome, complications, and quality of life. Methods: Thirty-eight patients (23 men, 15 women; mean age 47 ± 19 years) with dorsal pelvic ring fractures (type-C-injuries after AO/OTA) that have been stabilized by either TIFI (group TIFI, n = 22) or SPF (group SPF, n = 16) between May 2015 and December 2018 were retrospectively reviewed. Outcome measurements included demographic data, perioperative parameters, and complications and were obtained from the medical information system. Quality of life was assessed using the German version of the short form 36 (SF-36) and short muskuloskeletal function assessment (SMFA-D). Clinical results were assessed using Merle d'Aubigne-Score, Iowa Pelvic Score, and Majeed Pelvic Score. Results: Both groups show relatively good post-operative results, which has previously been reported. Quality of life was comparable in both groups. Group TIFI was slightly superior regarding complication rates, cutting/suture time, and fluoroscopy time. Group SPF seemed to be superior regarding pain and pelvic scores. Conclusion: None of the methods could demonstrate significant superiority over the other. Management of pelvic injuries remains a highly individual challenge adapted to the individual patients' condition. Nevertheless, if fractures allow for stabilization with TIFI, the use of this method should be taken into consideration as a less invasive and more tissue-conserving approach

Correction of severe valgus osteoarthritis by total knee arthroplasty is associated with increased postoperative ankle symptoms

Purpose: The aim of this study was to assess the mid-term clinical outcome of the ankle joint after total knee arthroplasty (TKA) in high-grade valgus osteoarthritis. Methods: In this case–control study, n=36 patients with a preoperative mechanical tibiofemoral angle (mTFA)≥15° who underwent TKA between December 2002 and December 2012 were included. The control group (mTFA<15°) of n=60 patients was created using case matching. Radiological [mechanical tibiofemoral angle (mTFA) and ankle joint orientation to the ground (G-AJLO)] and clinical parameters [Foot Function Index (FFI), Knee Society Score, Forgotten Joint Score, and Range of Motion (ROM)] were analysed. The mean follow-up time was 59 months (IQR [56, 62]). Results: The degree of correcting the mTFA by TKA signifcantly correlated with the postoperative FFI (R=0.95, p<0.05), although the knee and ankle joint lines were corrected to neutral orientations. A cut-of value of 16.5° [AUC 0.912 (0.85–0.975 95% CI), sensitivity=0.8, specifcity=0.895] was calculated, above which the odds ratio (OR) for developing ankle symptoms increased vastly [OR 34.0 (9.10–127.02 95% CI)]. ROM restrictions of the subtalar joint displayed a strong sig nifcant correlation with the FFI (R=0.74, p<0.05), demonstrating that decreased ROM of the subtalar joint was associated with aggravated outcomes of the ankle joint. Conclusions: In this study, higher degrees of leg axis correction in TKA were associated with increased postoperative ankle symptoms. When TKA is performed in excessive valgus knee osteoarthritis, surgeons should be aware that this might trigger the onset or progression of ankle symptoms, particularly in cases of a stif subtalar joint. Level of evidence III

Time-Dependent Alterations of MMPs, TIMPs and Tendon Structure in Human Achilles Tendons after Acute Rupture

A balance between matrix metalloproteinases (MMPs) and their inhibitors (TIMPs) is required to maintain tendon homeostasis. Variation in this balance over time might impact on the success of tendon healing. This study aimed to analyze structural changes and the expression profile of MMPs and TIMPs in human Achilles tendons at different time-points after rupture. Biopsies from 37 patients with acute Achilles tendon rupture were taken at surgery and grouped according to time after rupture: early (2–4 days), middle (5–6 days), and late (≥7 days), and intact Achilles tendons served as control. The histological score increased from the early to the late time-point after rupture, indicating the progression towards a more degenerative status. In comparison to intact tendons, qRT-PCR analysis revealed a significantly increased expression of MMP-1, -2, -13, TIMP-1, COL1A1, and COL3A1 in ruptured tendons, whereas TIMP-3 decreased. Comparing the changes over time post rupture, the expression of MMP-9, -13, and COL1A1 significantly increased, whereas MMP-3 and -10 expression decreased. TIMP expression was not significantly altered over time. MMP staining by immunohistochemistry was positive in the ruptured tendons exemplarily analyzed from early and late time-points. The study demonstrates a pivotal contribution of all investigated MMPs and TIMP-1, but a minor role of TIMP-2, -3, and -4, in the early human tendon healing process. View Full-Tex

Decision support by machine learning systems for acute management of severely injured patients: A systematic review

Introduction Treating severely injured patients requires numerous critical decisions within short intervals in a highly complex situation. The coordination of a trauma team in this setting has been shown to be associated with multiple procedural errors, even of experienced care teams. Machine learning (ML) is an approach that estimates outcomes based on past experiences and data patterns using a computer-generated algorithm. This systematic review aimed to summarize the existing literature on the value of ML for the initial management of severely injured patients. Methods We conducted a systematic review of the literature with the goal of finding all articles describing the use of ML systems in the context of acute management of severely injured patients. MESH search of Pubmed/Medline and Web of Science was conducted. Studies including fewer than 10 patients were excluded. Studies were divided into the following main prediction groups: (1) injury pattern, (2) hemorrhage/need for transfusion, (3) emergency intervention, (4) ICU/length of hospital stay, and (5) mortality. Results Thirty-six articles met the inclusion criteria; among these were two prospective and thirty-four retrospective case series. Publication dates ranged from 2000 to 2020 and included 32 different first authors. A total of 18,586,929 patients were included in the prediction models. Mortality was the most represented main prediction group (n = 19). ML models used were artificial neural network ( n = 15), singular vector machine (n = 3), Bayesian network (n = 7), random forest (n = 6), natural language processing (n = 2), stacked ensemble classifier [SuperLearner (SL), n = 3], k-nearest neighbor (n = 1), belief system (n = 1), and sequential minimal optimization (n = 2) models. Thirty articles assessed results as positive, five showed moderate results, and one article described negative results to their implementation of the respective prediction model. Conclusions While the majority of articles show a generally positive result with high accuracy and precision, there are several requirements that need to be met to make the implementation of such models in daily clinical work possible. Furthermore, experience in dealing with on-site implementation and more clinical trials are necessary before the implementation of ML techniques in clinical care can become a reality