本文以航天工程大学考博英语经典真题为例，作为 2026 年航天工程大学考博英语真题的样题参考，帮助考生掌握考博英语阅读理解、翻译、写作等核心题型的深度解析逻辑，契合博士研究生对 “语言精准性 + 逻辑思辨性 + 学术表达规范性” 的能力要求。
The development of aerospace technology has always been closely linked to national security and scientific progress. In recent decades, with the rapid advancement of artificial intelligence and big data, the aerospace industry has entered a new era of intelligent development. Unlike traditional aerospace engineering, which mainly relies on manual design and simulation, modern aerospace systems integrate advanced technologies such as machine learning, autonomous navigation, and real-time data analysis to improve operational efficiency and reliability.
One of the key applications of AI in aerospace is autonomous mission planning. For complex space missions, such as deep space exploration or satellite constellation deployment, AI algorithms can quickly optimize mission routes, allocate resources reasonably, and respond to unexpected emergencies in real time. For example, NASA's Mars rovers use AI to navigate rough terrain, avoid obstacles, and complete scientific exploration tasks independently. This not only reduces the workload of ground control personnel but also enhances the adaptability of the rovers to extreme environments.
Another important trend is the use of big data in aerospace maintenance. By collecting and analyzing data from aircraft engines, satellite components, and other key parts during operation, engineers can predict potential failures in advance and perform preventive maintenance. This predictive maintenance model has been widely adopted by major aerospace companies, significantly reducing maintenance costs and improving the safety of aerospace systems.
However, the intelligent transformation of the aerospace industry also faces challenges. Cybersecurity risks have become a major concern, as intelligent aerospace systems are more vulnerable to cyber attacks. In addition, the lack of professionals with both aerospace engineering and AI expertise has hindered the rapid development of intelligent aerospace technology. To address these issues, governments and enterprises around the world have increased investment in aerospace cybersecurity research and talent training programs.
Questions:
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What is the main difference between modern aerospace systems and traditional ones?
[A] Modern systems focus more on national security.
[B] Modern systems integrate advanced intelligent technologies.
[C] Traditional systems rely on big data analysis.
[D] Traditional systems are more efficient in mission planning.
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Why is AI used in autonomous mission planning for space missions?
[A] To reduce the cost of space exploration.
[B] To replace ground control personnel completely.
[C] To optimize routes, allocate resources and respond to emergencies.
[D] To improve the communication between rovers and ground stations.
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How does big data contribute to aerospace maintenance?
[A] By designing more reliable aerospace components.
[B] By predicting potential failures and enabling preventive maintenance.
[C] By reducing the weight of aerospace systems.
[D] By simplifying the maintenance process for ground personnel.
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What is one of the challenges faced by the intelligent transformation of the aerospace industry?
[A] The high cost of AI technology.
[B] Cybersecurity risks and talent shortages.
[C] The complexity of space missions.
[D] The lack of government support.
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What is the main idea of the passage?
[A] The history of aerospace technology development.
[B] The applications and challenges of intelligent technology in aerospace.
[C] The importance of national security in aerospace development.
[D] The role of NASA in promoting aerospace technology.
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答案 B（Modern systems integrate advanced intelligent technologies.）
细节定位与逻辑推导：定位原文第一段核心表述 “Unlike traditional aerospace engineering, which mainly relies on manual design and simulation, modern aerospace systems integrate advanced technologies such as machine learning, autonomous navigation, and real-time data analysis”，明确现代航天系统与传统系统的核心区别是 “融合先进智能技术”，选项 B 精准匹配这一信息。
干扰项排除：A “现代系统更注重国家安全” 与原文首句 “航天技术发展一直与国家安全紧密相关” 不符，国家安全是两者共同的关联点，非区别；C “传统系统依赖大数据分析” 与原文 “传统系统依赖人工设计和模拟” 矛盾；D “传统系统在任务规划上更高效” 无原文依据，原文未对比两者效率差异。
学术扩展：考博英语阅读理解的 “区别类” 题目，需重点关注原文中 “unlike”“different from” 等转折对比词，快速锁定差异核心信息。
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答案 C（To optimize routes, allocate resources and respond to emergencies.）
例证目的与细节匹配：定位原文第二段 “AI algorithms can quickly optimize mission routes, allocate resources reasonably, and respond to unexpected emergencies in real time”，直接说明 AI 用于自主任务规划的目的，选项 C 完整涵盖该内容。
干扰项排除：A “降低太空探索成本” 原文未提及；B “完全替代地面控制人员” 与原文 “reduces the workload of ground control personnel”（减轻工作量）不符，“完全替代” 表述绝对；D “改善漫游者与地面站的通信” 并非 AI 在任务规划中的作用，属于无关信息。
学术扩展：解答 “目的类” 题目时，需注意原文中 “can”“to” 等表功能、目的的词汇，精准定位答案出处。
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答案 B（By predicting potential failures and enabling preventive maintenance.）
细节定位与语义验证：定位原文第三段 “By collecting and analyzing data... engineers can predict potential failures in advance and perform preventive maintenance”，明确大数据在航天维护中的作用是 “预测潜在故障并开展预防性维护”，选项 B 与原文语义一致。
干扰项排除：A “设计更可靠的航天部件”、C “减轻航天系统重量”、D “简化地面人员维护流程” 原文均未涉及，属于无中生有。
学术扩展：细节题中 “how” 引导的问句，答案通常在原文中以 “by + 动名词” 的结构呈现，需重点关注此类表达。
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答案 B（Cybersecurity risks and talent shortages.）
细节归纳与信息整合：定位原文第四段 “Cybersecurity risks have become a major concern... In addition, the lack of professionals... has hindered the rapid development”，归纳可知面临的挑战是 “网络安全风险” 和 “人才短缺”，选项 B 全面概括这两点。
干扰项排除：A “AI 技术成本高”、C “太空任务的复杂性”、D “缺乏政府支持” 原文均未提及，不符合题意。
学术扩展：解答 “挑战类” 题目时，需注意原文中 “however”“but” 等转折词后的内容，同时关注 “in addition”“also” 等表并列的词汇，避免遗漏关键信息。
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答案 B（The applications and challenges of intelligent technology in aerospace.）
主旨提炼与逻辑梳理：全文第一段引出航天行业智能化发展的背景，第二、三段介绍智能技术（AI、大数据）在航天领域的应用，第四段指出智能化转型面临的挑战，核心围绕 “智能技术在航天中的应用与挑战” 展开，选项 B 准确概括主旨。
干扰项排除：A “航天技术发展的历史” 原文未追溯历史，聚焦现代智能化发展；C “国家安全在航天发展中的重要性” 仅在首句提及，非全文核心；D “NASA 在推动航天技术中的作用” 仅为第二段例证，不能概括全文。
学术扩展：主旨题需把握 “总 - 分” 或 “总 - 分 - 总” 的文章结构，重点关注首尾段及各段首句，提炼核心话题与逻辑脉络。
Aerospace engineering is a highly interdisciplinary field that combines principles of mechanical engineering, electrical engineering, computer science, and materials science. With the continuous exploration of outer space, the demand for more efficient, reliable, and cost-effective aerospace systems is increasing. The development of reusable launch vehicles has greatly reduced the cost of space transportation, making space tourism and commercial space exploration a reality. At the same time, the research on advanced materials has played a crucial role in improving the performance and service life of aerospace components. In the future, aerospace technology will continue to break through technical bottlenecks, promoting the progress of human society and expanding the boundaries of human exploration.
航天工程是一门高度跨学科的领域，融合了机械工程、电气工程、计算机科学和材料科学的原理。随着人类对太空的持续探索，对更高效、可靠且具成本效益的航天系统的需求日益增长。可重复使用运载火箭的发展大幅降低了太空运输成本，使太空旅游和商业太空探索成为现实。与此同时，先进材料的研究在提升航天部件性能和使用寿命方面发挥了关键作用。未来，航天技术将持续突破技术瓶颈，推动人类社会进步，拓展人类探索的边界。
- 句式拆分与优化：原文首句为复合句，“that” 引导定语从句修饰 “field”，翻译时拆分为主谓宾结构 + 后置定语，符合中文表达习惯；“highly interdisciplinary” 译为 “高度跨学科的”，精准传递核心含义。
- 专业术语翻译：“reusable launch vehicles” 译为 “可重复使用运载火箭”，“commercial space exploration” 译为 “商业太空探索”，均为航天领域标准术语，保证翻译专业性。
- 逻辑衔接处理：“At the same time” 译为 “与此同时”，“In the future” 译为 “未来”，使段落逻辑连贯；“promoting the progress of human society and expanding the boundaries of human exploration” 译为并列动宾结构，句式对称流畅。
- 语义精准传递：“cost-effective” 译为 “具成本效益的”，既体现 “成本低” 又强调 “效果好”；“play a crucial role in” 译为 “发挥关键作用”，符合中文表达习惯，避免直译生硬感。
学术扩展：考博英语翻译需兼顾专业性与流畅性，针对科技类文本，要积累专业术语，拆分复杂句式，同时注重逻辑衔接词的合理运用，确保译文准确传达原文含义。
Directions: Write an essay of 250-300 words on the topic "The Impact of Artificial Intelligence on Aerospace Engineering". You should support your views with relevant examples.
The Impact of Artificial Intelligence on Aerospace Engineering
Artificial intelligence (AI) has emerged as a transformative force in aerospace engineering, reshaping the way we design, operate, and maintain aerospace systems. Its impact is profound and far-reaching, bringing both unprecedented opportunities and new challenges.
On the positive side, AI has significantly improved the efficiency and reliability of aerospace missions. In aircraft design, AI-powered simulation tools can quickly test thousands of design schemes, optimizing aerodynamic performance and reducing development cycles. For instance, major aerospace manufacturers use AI algorithms to simulate airflow around aircraft wings, leading to more fuel-efficient and environmentally friendly designs. In space exploration, AI enables autonomous navigation for satellites and rovers, allowing them to complete complex tasks without constant human intervention. NASA's Perseverance rover, equipped with AI technology, successfully collected Martian soil samples and conducted scientific experiments independently.
However, AI also poses challenges to the aerospace industry. Cybersecurity threats are a top concern, as AI-driven systems are vulnerable to hacking and data breaches. Additionally, the ethical implications of autonomous aerospace systems, such as decision-making in emergency situations, require careful consideration.
In conclusion, AI has become an indispensable part of modern aerospace engineering. To fully leverage its potential, the industry must address cybersecurity and ethical issues while investing in talent training. With continuous innovation and proper regulation, AI will continue to drive the development of aerospace engineering to new heights.
- 结构框架：文章采用 “总 - 分 - 总” 结构，开篇点明 AI 对航天工程的变革性影响，中间分述积极作用与挑战，结尾总结并提出建议，逻辑清晰，符合考博写作思辨性要求。
- 论证方式：通过 “举例论证” 增强说服力，列举航空设计中 AI 模拟工具的应用、毅力号火星车的案例，使观点更具体可信；同时采用 “对比论证”，客观分析 AI 的利弊，体现思维全面性。
- 语言表达：使用 “transformative force”“profound and far-reaching”“indispensable part” 等学术词汇，提升文章专业性；句式多样，包含定语从句、状语从句等复杂句式，符合博士研究生学术表达规范。
- 主题契合：紧扣 “AI 对航天工程的影响” 核心话题，既涵盖技术应用层面，也涉及安全、伦理等深层问题，立意深刻，满足写作要求。
学术扩展：考博英语写作需构建清晰的逻辑框架，积累科技类话题相关素材与学术词汇，善于运用举例、对比等论证方法，同时关注话题的多维度分析，提升文章思辨性与深度。
- 主旨题关注首尾段及各段首句，提炼 “核心话题 + 作者立场”，避免被局部例证误导。
- 细节题通过 “关键词定位法” 锁定原文，重点验证选项与原文的语义一致性，警惕偷换概念、语义绝对化等干扰项。
- 态度题结合作者的论证逻辑与情感色彩词汇（如褒贬义词、转折词）判断倾向，避免主观臆断。
- 英译汉时，拆分英文长句，优化中文句式，保留原文专业术语的准确性，避免直译导致的生硬感。
- 积累航天、科技类高频词汇与固定表达，提升翻译的专业性；关注逻辑衔接词的合理转换，使译文连贯自然。
- 每日练习 1 段科技类英文段落翻译，对照参考译文修正表达偏差，总结句式转换技巧。
- 针对科技类话题，采用 “现象引入” 开篇，明确核心观点，增强文章吸引力。
- 论证时从 “积极影响 + 潜在挑战” 或 “技术应用 + 发展前景” 多维度展开，结合具体案例支撑观点，避免空泛论述。
- 每周仿写 1 篇真题作文，重点修正语法错误与逻辑漏洞，控制字数在 250-300 词，提升学术语言表达能力。
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