Physics-based Modelling for Aircraft Noise and Emission Predictions

Starting from semi-empirical noise source models for the aircraft and 4D trajectory computations, this work focuses on the environmental assessment of scenario studies regarding technology evaluation and procedural planning. Extensive work was performed on improving and validating the existing tools. The physics based dynamic modelling for straight inflight was extended to account for a third space dimension and the inclusion of non-zero wind. Real flight data were used for model verification. Ground noise measurements were used to validate the physics-based prediction of source noise for varying operating conditions and to adapt the model to a state-of-the-art aircraft and engine. In this thesis, a summary of the developed physics-based methods and their validation are presented and the selected case studies are described.An important part of the presented research focused on sustainability aspects and the evaluation of interdependencies between noise, NOx and CO2 emissions. New propulsion system designs were generated for a state-of-the-art ultra-high bypass ratio turbofan engine by allowing variation in the OPR (Overall Pressure Ratio), FPR (Fan Pressure Ratio) and BPR (Bypass Ratio). By varying these parameters, the engine was optimized for minimum installed specific fuel consumption. Allowing minimum fuel burn variation around this optimal point, different engine designs and operational characteristics were established and trades between LTO (Landing and Take-off) NOx emissions and cumulative noise were examined.Another aspect focusing on the sustainability of air transport concerns the operational level, where the aim is to establish improved procedures and trajectories through the use of the existing technology. Several noise abatement procedures already exist and are implemented to reduce pollution around airports. Focusing on approach procedures, these standard operations were evaluated for noise and emissions. More advanced procedures were designed and assessed for their environmental impact and optimization was carried out to establish the optimal procedure for specific cases. It was demonstrated that quantifying these trade-offs and adapting the design to specific conditions is essential when new flight procedures are designed

Quantifying the Environmental Design Trades for a State-of-the-Art Turbofan Engine

Aircraft and engine technology have continuously evolved since their introduction and significant improvement has been made in fuel efficiency, emissions, and noise reduction. One of the major issues that the aviation industry is facing today is pollution around the airports, which has an effect both on human health and on the climate. Although noise emissions do not have a direct impact on climate, variations in departure and arrival procedures influence both CO2 and non-CO2 emissions. In addition, design choices made to curb noise might increase CO2 and vice versa. Thus, multidisciplinary modeling is required for the assessment of these interdependencies for new aircraft and flight procedures. A particular aspect that has received little attention is the quantification of the extent to which early design choices influence the trades of CO2, NOx, and noise. In this study, a single aisle thrust class turbofan engine is optimized for minimum installed SFC (Specific Fuel Consumption). The installed SFC metric includes the effect of engine nacelle drag and engine weight. Close to optimal cycles are then studied to establish how variation in engine cycle parameters trade with noise certification and LTO (Landing and Take-Off) emissions. It is demonstrated that around the optimum a relatively large variation in cycle parameters is allowed with only a modest effect on the installed SFC metric. This freedom in choosing cycle parameters allows the designer to trade noise and emissions. Around the optimal point of a state-of-the-art single aisle thrust class propulsion system, a 1.7 dB reduction in cumulative noise and a 12% reduction in EINOx could be accomplished with a 0.5% penalty in installed SFC

Environmental Assessment of Noise Abatement Approach Trajectories

Noise abatement procedures are one of the main actions implemented to reduce noise pollution around airports. In this study, the focus is turned on approach operations and their environmental impact. The assessment starts from standard optimized procedures, namely the Continuous Descent Approach (CDA) and the Low Drag Low Power (LDLP) and the aim is to look into more advanced procedures, such as a Steep and a Segmented CDA, an Advanced LDLP and an optimized trajectory for the specific flight conditions. The procedures are designed for an A321neo and compared and evaluated for noise and emissions. It is demonstrated that multidisciplinary design and adaptation to specific conditions are required for the assessment of these interdependencies for flight procedures

Lean back and wait for the alarm? Testing an automated alarm system for nosocomial outbreaks to provide support for infection control professionals

INTRODUCTION: Outbreaks of communicable diseases in hospitals need to be quickly detected in order to enable immediate control. The increasing digitalization of hospital data processing offers potential solutions for automated outbreak detection systems (AODS). Our goal was to assess a newly developed AODS. METHODS: Our AODS was based on the diagnostic results of routine clinical microbiological examinations. The system prospectively counted detections per bacterial pathogen over time for the years 2016 and 2017. The baseline data covers data from 2013-2015. The comparative analysis was based on six different mathematical algorithms (normal/Poisson and score prediction intervals, the early aberration reporting system, negative binomial CUSUMs, and the Farrington algorithm). The clusters automatically detected were then compared with the results of our manual outbreak detection system. RESULTS: During the analysis period, 14 different hospital outbreaks were detected as a result of conventional manual outbreak detection. Based on the pathogens' overall incidence, outbreaks were divided into two categories: outbreaks with rarely detected pathogens (sporadic) and outbreaks with often detected pathogens (endemic). For outbreaks with sporadic pathogens, the detection rate of our AODS ranged from 83% to 100%. Every algorithm detected 6 of 7 outbreaks with a sporadic pathogen. The AODS identified outbreaks with an endemic pathogen were at a detection rate of 33% to 100%. For endemic pathogens, the results varied based on the epidemiological characteristics of each outbreak and pathogen. CONCLUSION: AODS for hospitals based on routine microbiological data is feasible and can provide relevant benefits for infection control teams. It offers in-time automated notification of suspected pathogen clusters especially for sporadically occurring pathogens. However, outbreaks of endemically detected pathogens need further individual pathogen-specific and setting-specific adjustments

Neural correlates of subjective arousal and valence in health and panic disorder

Aberrant emotion processing is a core characteristic of panic disorder (PD). Findings concerning the underlying neural pathways remain inconsistent. We applied functional magnetic resonance imaging (fMRI) in the context of a task based on the circumplex model of affect. This model links affective states to two underlying neurophysiological systems: arousal and valence. Twenty-two healthy participants and 20 participants with PD rated arousal and valence in response to affective faces during fMRI. In healthy controls, we found that arousal modulated the hemodynamic response in the parahippocampus, the ventromedial prefrontal cortex and the cuneus during face perception. Valence and extreme ratings of valence modulated the hemodynamic response in temporal, parietal, somatosensory, premotor and cerebellar regions. Comparing healthy controls to participants with PD, we found that healthy controls showed a stronger modulation of the hemodynamic response during face perception associated with extreme ratings of valence in the parahippocampus and the supplementary motor area. This suggests parahippocampal dysfunction in the processing of highly valenced affective faces in PD, which may underlie aberrant contextualization of strong affective stimuli. Our findings need to be interpreted with care as they were adjusted for multiple comparisons using a liberal correction procedure

Identifying well‐being profiles and resilience characteristics in ex‐members of fundamentalist Christian faith communities

There is a lack of empirical research on the heterogeneity in well-being of individuals who disaffiliated (i.e., left or were expelled) from an exclusionary and demanding faith community. Thus, little quantitative knowledge exists on factors related to resilience in these individuals. Therefore, the study aims were twofold: (1) to identify profiles of well-being in ex-members; and (2) to examine the characteristics of the identified profiles. A cross-sectional online survey assessed ex-members of various fundamentalist Christian faith communities. Latent profile analysis identified latent heterogeneity within the sample. Well-being profile indicators included perceived stress, psychopathological symptoms, affect, and satisfaction with life. Profile-related characteristics included socio-demographics (i.e., gender, age), membership (i.e., reason for joining, duration, extent of involvement, reasons for exit, social support during exit, and time since the exit), and resilience-supporting resources (i.e., social support, self-esteem, sense of coherence, personality, socio-economic status). In the final sample (N = 622, Mage = 41.34 years; 65.60% female), four distinct profiles were identified: resilient (25.70%), normative (36.40%), vulnerable (27.20%), and adverse (10.70%). The resilient profile was characterised by higher age, lower reporting of abuse or maltreatment as exit reason, and highest levels of resilience-supporting resources. Ex-members of fundamentalist Christian faith communities differ substantially in their well-being. Membership aspects were only weakly related to current well-being, with the exception of the exit reason of abuse or maltreatment. This study provided novel quantitative insights into the well-being profiles of individuals who disaffiliated from a fundamentalist Christian faith community in German-speaking countries

Implementation of an automated cluster alert system into the routine work of infection control and hospital epidemiology: experiences from a tertiary care university hospital

Background: Early detection of clusters of pathogens is crucial for infection prevention and control (IPC) in hospitals. Conventional manual cluster detection is usually restricted to certain areas of the hospital and multidrug resistant organisms. Automation can increase the comprehensiveness of cluster surveillance without depleting human resources. We aimed to describe the application of an automated cluster alert system (CLAR) in the routine IPC work in a hospital. Additionally, we aimed to provide information on the clusters detected and their properties. Methods: CLAR was continuously utilized during the year 2019 at Charite university hospital. CLAR analyzed microbiological and patient-related data to calculate a pathogen-baseline for every ward. Daily, this baseline was compared to data of the previous 14 days. If the baseline was exceeded, a cluster alert was generated and sent to the IPC team. From July 2019 onwards, alerts were systematically categorized as relevant or non-relevant at the discretion of the IPC physician in charge. Results: In one year, CLAR detected 1,714 clusters. The median number of isolates per cluster was two. The most common cluster pathogens were Enterococcus faecium (n = 326, 19 %), Escherichia coli (n = 274, 16 %) and Enterococcus faecalis (n = 250, 15 %). The majority of clusters (n = 1,360, 79 %) comprised of susceptible organisms. For 906 alerts relevance assessment was performed, with 317 (35 %) alerts being classified as relevant. Conclusions: CLAR demonstrated the capability of detecting small clusters and clusters of susceptible organisms. Future improvements must aim to reduce the number of non-relevant alerts without impeding detection of relevant clusters. Digital solutions to IPC represent a considerable potential for improved patient care. Systems such as CLAR could be adapted to other hospitals and healthcare settings, and thereby serve as a means to fulfill these potentials

Intimate partner violence as a predictor of marital disruption in rural Rakai, Uganda: a longitudinal study.

ObjectivesWe assessed the association between intimate partner violence (IPV) and union disruption (divorce or separation) in the rural Ugandan setting of Rakai District.MethodsWe analyzed longitudinal data collected from April 1999 to June 2006, from 6834 women (15-49 years) living in 50 communities in Rakai. Participants were either officially married, traditionally married or in a consensual union during one or more surveys and completed at least one follow-up survey. The primary outcome was union disruption through divorce or separation from the primary sexual partner.ResultsPast year IPV ranged from 6.49 % (severe physical abuse) to 31.99 % (emotional abuse). Severe physical IPV was significantly associated with divorce/separation, after adjusting for other covariates (aOR = 1.80, 95 % CI 1.01-3.22). Another predictor of union disruption was a woman having two or more sexual partners in the past year (aOR = 8.42, 95 % CI 5.97-11.89). Factors protecting against divorce/separation included an increasing number of co-resident biological children and longer duration of union.ConclusionsIPV, particularly severe physical abuse, is an important risk factor for union disruption. Marital counseling, health education and interventions should address the role of IPV on the wellbeing of women and the stability of couples in Uganda